Computational Intelligence

Topics are

• Ant Colony Optimization
• Artificial Immune Systems
• Simulated Annealing
• Swarm Intelligence
• Differential Evolution
• Tabu Search
• Scatter Search
• Random Search
• Rough Sets
• Approximate Reasoning
• Fuzzy Control
• Fuzzy Neural Networks
• Fuzzy Systems for Approximation
• Neural Networks for Approximation
• Generating Fuzzy Rules
• Genetic Fuzzy Systems
• Neural Networks for Time Series
• Computational Intelligence in Education
• Fuzzy Dynamical Systems
• Hybrid Methods

 

\begin{equation}{\label{a}}\tag{A}\mbox{}\end{equation}

Ant Colony Optimization.

\begin{enumerate}

\item Abbass, H.A., Hoai, X. and McKay, R.I.:
AntTAG: A New Method to Compose Computer Programs Using Colonies of Ants,
{\em Proceedings of the IEEE Congress on Evolutionary Computation} (2002)
1654-1659.

\item Badr, A. and Fahmy, A.:
A Proof of Convergence for Ant Algorithms,
{\em Information Sciences} 160 (2004) 267-279.

\item Bahreininejad, A.:
A Hybrid Ant Colony Optimization Approach for Finite Element Mesh
Decomposition,
{\em structural and Multidisciplinary Optimization} 28 (2004) 307-316.

\item Blum, C.:
Beam-ACO — Hybridizing Ant Colony Optimization with Beam Search:
An Application to Open Shop Scheduling,
{\em Computers and OPerations Research} 32 (2005) 1565-1591.

\item Blum, C. and Dorigo, M.:
Search Bias in Ant Colony Optimization: On the Role of Competition-Balanced Systems,
{\em IEEE Transactions on Evolutionary Computation} 9 (2005) 159-174.

\item Blum, C., Vall\'{e}s, M.Y. and Blesa, M.J.:
An Ant Colony Optimization Algorithm for DNA Sequencing by Hybridization,
{\em Computers and Operations Research} 35 (2008) 3620-3635.

\item Boryczka, M. and Czech, Z.J.:
Solving Approximation Problems by Ant Colony Programming,
{\em Proceedings of the IEEE Genetic and Evolutionary COmputation Conference} (2002).

\item Bullnheimer, B., Hartl, R.F. and Strauss, C.:
An Improved Ant System Algorithm for the Vehicle Routing Problem,
{\em Annals of Operations Research} 89 (1999) 319-328.

\item Cheng, C.-B. and Mao, C.-P.:
A Modified Ant Colony System for Solving the Travelling Salesman Problem with Time Windows,
{\em Mathematical and Computer Modelling} 46 (2007) 1225-1235.

\item Chu, S.-C., Roddick, J.F. and Pan, J.-S.:
Ant Colony System with Communication Strategies,
{\em Information Sciences} 167 (2004) 63-76.

\item de Campos, L.M., Fern\'{a}ndez-Luna, J.M., G\'{a}mez, J.A. and Puerta, J.M.:
Ant Colony Optimization for Learning Bayesian Networks,
{\em International Journal of Approximate Reasoning} 31 (2002) 291-311.

\item Demirel, N.C. and Toksari, M.D.:
Optimization of the Quadratic Assignment Problem Using an Ant Colony
Algorithm,
{\em Applied Mathematics and Computation} 183 (2006) 427-435.

\item Doerner, K., Gutjahr, W.J., Hart, R.F., Strauss, C. and Stummer, C.:
Pareto Ant Colony Optimization: A Metaheuristic Approach to Multiobjective
Portfolio Selection,
{\en Annals of Operations Research} 131 (2004) 79-99.

\item Doerner, K., Gutjahr, W.J., Hartl, R.F., Strauss, C. and Stummer, C.:
Pareto Ant Colony Optimization with ILP Preprocessing in Multiobjective
Project Portfolio Selection,
{\em European Journal of Operational Research} 171 (2006) 830-841.

\item Dorigo, M., Bonabeau, E. and Theraulaz, G.:
Ant Algorithms and Stigmery,
{\em Future Generation Computer Systems} 16 (2000) 851-871.

\item Dorigo, M., Di Caro, G. and Gambardella, L.M.:
Ant Algorithms for Discrete Optimization,
{\em Artificial Life} 5 (1999) 137-172.

\item Dorigo, M. and Gambardella, L.M.:
Ant Colony System: A Cooperative Learning Approach to the Traveling
Salesman Problem,
{\em IEEE Trans. on Evolutionary Computation} 1 (1997) 53-66.

\item Dorigo, M. and Gambardella, L.M.: (Ant Colony Optimization)
Ant Colonies for the Traveling Salesman Problem,
{\em BioSystems} 43 (1997) 73-81.

\item Dorigo, M., Maniezzo, V. and Colorni, A.:
Ant System: Optimization by a Colony of Cooperative Agents,
{\em IEEE Trans. on Systems, Man, and Cybernetics — Part B} 26 (1996) 29-41.

\item Dr\'{e}o, J. and Siarry, P.:
An Ant Colony Algorithm Aimed at Dynamic Continuous Optimization,
{\em Applied Mathematics and Computation} 181 (2006) 457-467.

\item Eggers, J., Feillet, Kehl, S., Wagner, M.O. and Yannou, B.:
Optimization of the Keybord Arrangement Problem Using an Ant Colony Algorithm,
{\em European Journal of Operational Research} 148 (2003) 672-686.

\item Gajpal, Y. and Rajendran, C.:
An Ant-Colony Optimization Algorithm for Minimizing the Completion-Time Variance of Jobs in Flowshops,
{\em International Journal of Production Economics} 101 (2006) 259-272.

\item Gambardella, L.M., Taillard, E.D. and Dorigo, M.:
An Colonies for the Quadratic Assignment Problem,
{\em The Journal of Operational Research Society} 50 (1999) 167-176.

\item Garc\'{i}a-Mart\'{i}nez, C., Cord\'{o}n, O. and Herrera, F.:
A Taxonomy and an Empirical Analysis of Multiple Objective Ant Colony Optimization Algorithms for the Bi-Criteria TSP,
{\em European Journal of Operational Research} 180 (2007) 116-148.

\item Gravel, M., Price, W.L. and Gagn\'{e}, C.:
Scheduling Continuous Casting of Aluminum Using a Multiple Objective Ant
Colony Optimization Metaheuristic,
{\em European Journal of Operational Research} 143 (2002) 218-229.

\item Gutjahr, W.J.:
A Graph-Based Ant System and Its Convergence,
{\em Future Generation Computer Systems} 16 (2000) 873-888.

\item Gutjahr, W.J.:
ACO Algorithm with Guaranteed Convergence to the Optimal Solution,
{\em Information Processing Letters} 82 (2002) 145-153.

\item Gutjahr, W.J.:
On the Finite-Time Dynamics of Ant Colony Optimization,
{\em Methodol. Comput. Appl. Prob.} 8 (2006) 105-133.

\item Gutjahr, W.J.:
First Steps to the Runtime Complexity Analysis of Ant Colony Optimization,
{\em Computers and Operations Research} 35 (2008) 2711-2727.

\item Jensen, R. and Shen, Q.:
Fuzzy-Rough Data Reduction with Ant Colony Optimization,
{\em Fuzzy Sets and Systems} 149 (2005) 5-20.

\item Li, L., Yang, Y. and Peng, H.:
Fuzzy System Identification via Chaotic Ant Swarm,
{\em Chaos, Solitions and Fractals} (2008)

\item Liao, C.-J. and Juan, H.-C.:
An Colony Optimization for Single-Machine Tardiness Scheduling with
Sequence-Dependent Setups,
{\em Computers and Operations Research} 34 (2007) 1899-1909.

\item McKendall, A.R. and Shang, J.:
Hybrid Ant Systems for the Dynamic Facility Layout Problem,
{\em Computers and Operations Research} 33 (2006) 790-803.

\item Merkle, D. and Middendorf, M.:
Modeling the Dynamics of Ant Colony Optimization,
{\em Evolutionary Computation} 10 (2002) 235-262.

\item Meuleau, N. and Dorigo, M.:
Ant Colony Optimization and Stochastic Gradient Descent,
{\em Artificial Life} 8 (2002) 103-121.

\item Middendorf, M., Reischle, F. and Schmeck, H.:
Multi Colony Ant Algorithms,
{\em Journal of Heuristics} 8 (2002) 305-320.

\item Montgomery, J., Randall, M. and Hendtlass, T.:
Solution Bias in Ant Colony Optimization: Lesson for Selecting
Pheromone Models,
{\em Computers and Operations Research} 35 (2008) 2728-2749.

\item Nahas, N. and Nourelfath, M.:
Ant System for Reliability Optimization of a Series System with
Multiple-Choice and Budget Constraints,
{\em Reliability Engineering and System Safety} 87 (2005) 1-12.

\item Rajendran, C. and Ziegler, H.:
Scheduling to Minimize the Sum of Weighted Flowtime and Weighted Tardiness of
Jobs in a Flowshop with Sequence-Dependent Setup Times,
{\em European Journal of Operational Research} 149 (2003) 513-522.

\item Rajendran, C. and Ziegler, H.:
Two Ant-Colony Algorithms for Minimizing Total Flowtime in Permutation
Flowshops,
{\em Computers and Operations Research} 48 (2005) 789-797.

\item Reimann, M., Doerner, K. and Hartl, R.F.:
D-Ants: Savings Based Ants Divide and Conquer the Vehicle Routing Problem,
{\em Computesr and Operations Research} 31 (2004) 563-591.

\item Samrout, M., Yalaoui, F., Chatelet, E. and Chebbo, N.:
New Methods to Minimize the Preventive Maintenance Cost of Series-Parallel
Systems Using Ant Colony Optimization,
{\em Reliability Engineering and System Safety} 89 (2005) 346-354.

\item Shelokar, P.S., Jayaraman, V.K. and Kulkarni, B.D.:
Ant Algorithm for Single and Multiobjective Reliability Optimization
Problems,
{\em Quality and Reliability Engineering International} 18 (2002) 497-514.

\item Shelokar, P.S., Siarry, P., Jayaraman, V.K. and Kulkarni, B.D.:
Particle Swarm and Ant Colony Algorithms Hybridzed for Improved
Continuous Optimization,
{\em Applied Mathematics and Computation} ?? (2006) ???.

\item Shyu, S.J., Lin, B.M.T. and Yin, P.Y.:
Application of Ant Colony Optimization for No-Wait Flowshop Scheduling
Problem to minimize the Total Completion Time,
{\em Computers and Operations Research} 47 (2004) 181-193.

\item Sitarz, S.:
Ant Algorithms and Simulated Annealing for Multicriteria Dynamic Programming,
{\em Computers and Operations Research} 36 (2009) 433-441.

\item Socha, K. and Dorigo, M.:
Ant Colony Optimization for Continuous Domain,
{\em European Journal of Operational Research} 185 (2008) 1155-1173.

\item Solimanpur, M., Vrat, P. and Shankar, R.:
Ant Colony Optimization Algorithm to the Inter-Cell Layout Problem in
Cellular Manufacturing,
{\em European Journal of Operational Research} 157 (2004) 592-606.

\item Solimanpur, M., Vrat, P. and Shankar, R.:
An Ant Algorithm for the Single Row Layout Problem in Flexible Manufacturing
Systems,
{\em Computesr and Operations Research} 32 (2005) 583-598.

\item St\”{u}tzle, T. and Dorigo, M.:
A Short Convergence Proof for a Class of Ant Colony Optimization Algorithms,
{\em IEEE Trans. On Evolutionary Computation} 6 (2002) 358-365.

\item St\”{u}tzle, T. and Hoos, H.H.:
MAX-MIN Ant System,
{\em Future Generation Computer Systems} 16 (2000) 889-914.

\item Toksari, M.D.:
Ant Colony Optimization for Finding the Global Minimum,
{\em Applied Mathematics and Computation} 176 (2006) 308-316.

\item Yin, P.-Y. and Wang, J.-Y.:
Ant Colony Optimization for the Nonlinear Resource Allocation Problem,
{\em Applied Mathematics and Computation} 174 (2006) 1438-1453.

\item Ying, K.-C. and Liao, C.-J.:
An ant Colony System for Permutation Flow-Shop Sequencing,
{\em Computers and Operations Research} 31 (2004) 791-801.

\item Zecchin, A.C., Simpson, A.R., Maier, H.R. and Nixon, J.B.:
Parametric Study for an Ant Algorithm Applied to Water Distribution System Optimization,
{\em IEEE Transactions on Evolutionary Computation} 9 (2005) 175-191.

\item Zlochin, M., Birattari, M., Seuleau, N. and Dorigo, M.:
Model-Based Search for Combinatorial Optimization: A Critical Survey,
{\em Annals of Operations Research} 131 (2004) 373-395.

\end{enumerate}

\begin{equation}{\label{b}}\tag{B}\mbox{}\end{equation}

Approximate Reasoning.

\begin{itemize}

\item Albert, P.:
The Albegra of Fuzzy Logic,
{\em Fuzzy Sets and Systems} 1 (1978) 203-230.

\item Baldwin, J.F.:
Fuzzy Logic and Approximate Reasoning for Mixed Input Arguments,
{\em Int. J. Man-Machine Studies} 11 (1979) 381-396.

\item Baldwin, J.F.:
A New Approach to Approximate Reasoning Using a Fuzzy Logic,
{\em Fuzzy Sets and Systems} 2 (1979) 309-325.

\item Baldwin, J.F. and Guild, N.C.F.:
Feasible Algorithms for Approximate Reasoning Using Fuzzy Logic,
{\em Fuzzy Sets and Systems} 3 (1980) 225-251.

\item Baldwin, J.F. and Pilsworth, B.W.:
Axiomatic Approach to Implication for Approximate Reasoning with Fuzzy Logic,
{\em Fuzzy Sets and Systems} 3 (1980) 193-219.

\item Boixader, D. and Jacas, J.:
Extensionality Based Approximate Reasoning,
{\em International Journal of Approximate Reasoning} 19 (1998) 221-230.

\item Buckley, J.J. \& Hayashi, Y. :
Can Approximate Reasoning be Consistent ?
{\em Fuzzy Sets and Systems} 65 (1994) 13-18.

\item Bustince, H.:
Indicator of Inclusion Grade for Interval-Valued Fuzzy Sets.
Application to Approximate Reasoning Based on Interval-Valued Fuzzy
Sets,
{\em International Journal of Approximate Reasoning} 23 (2000) 137-209.

\item Chang, T.C., Hasegawa, K. and Ibbs, C.W.:
The Effects of Membership Function on Fuzzy Reasoning,
{\em Fuzzy Sets and Systems} 44 (1991) 169-186.

\item Chen, S.-M., Hsiao, W.-H. and Jong, W.-T.:
Bidirectional Approximate Reasoning Based on Interval-Valued Fuzzy Sets,
{\em Fuzzy Sets and Systems} 91 (1997) 339-353.

\item Chun, M.-G.:
A Similarity-Based Bidirectional Approximate Reasoning Method for
Decision-Making Systems,
{\em Fuzzy Sets and Systems} 117 (2001) 269-278.

\item Cord\'{o}n, O., del Jesus, M.J. and Herrera, F.:
A Proposal on Reasoning Methods in Fuzzy Rule-Based Classification
Systems,
{\em International Journal of Approximate Reasoning} 20 (1999) 21-45.

\item Czogala, E.:
An Introduction to Probabilistic L-Valued Logic,
{\em Fuzzy Sets and Systems} 13 (1984) 179-185.

\item Czogala, E. and Leski, J.:
On Equivalence of Approximate Reasoning Results Using Different Interpretations
of Fuzzy If-Then Rules,
{\em Fuzzy Sets and Systems} 117 (2001) 279-296.

\item Denoeux, T.:
Reasoning with Imprecise Belief Structures,
{\em International Journal of Approximate Reasoning} 20 (1999) 79-111.

\item Dubois, D. and Prade, H.:
Fuzzy Sest in Approximate Reasoning, Part I:
Inference with Possibility Distributions,
{\em Fuzzy Sets and Systems} 40 (1991) 143-202.

\item Dubois, D. and Prade, H.:
Fuzzy Sets in Approximate Reasoning, Part II:
Logical Approaches,
{\em Fuzzy Sets and Systems} 40 (1991) 203-244.

\item Dubois, D. and Prade, H.:
Gradual Inference Rules in Approximate Reasoning,
{\em Information Sciences} 61 (1992) 193-122.

\item Dujet, C. and Vincemt, N.:
Force Implications: A New Approach to Human Reasoning,
{\em Fuzzy Sets and Systems} 69 (1995) 53-63.

\item Ebrahim, R.:
Fuzzy Logic Programming,
{\em Fuzzy Sets and Systems} 117 (2001) 215-230.

\item Eslami, E. and Buckley, J.J.:
Inverse Approximation Reasoning,
{\em Fuzzy Sets and Systems} 87 (1997) 155-158.

\item Eslami, E. and Buckley, J.J.:
Inverse Approximation Reasoning II: Maximize Entropy,
{\em Fuzzy Sets and Systems} 87 (1997) 291-295.

\item Fan, L.:
Discussion on “Some Methods fo Reasoning for Fuzzy Conditional
Propositions”,
{\em Fuzzy Sets and Systems} 86 (1997) 391-392.

\item Filev, D.P. and Yager, R.R.:
Operations on Fuzzy Numbers via Fuzzy Reasoning,
{\em Fuzzy Sets and Systems} 91 (1997) 137-142.

\item Giles, R.:
A Formal System for Fuzzy Reasoning,
{\em Fuzzy Sets and Systems} 2 (1979) 233-257.

\item Gorzalczany, M.B.:
A Method of Inference in Approximate Reasoning Based on Interval-Valued
Fuzzy Sets,
{\em Fuzzy Sets and Systems} 21 (1987) 1-17.

\item Gottwald, S.:
Fuzzy Propositional Logics,
{\em Fuzzy Sets and Systems} 3 (1980) 181-192.

\item Gupta, M.M. and Qi, J.:
Theory of $T$-Norms and Fuzzy Inference Methods,
{\em Fuzzy Sets and Systems} 40 (1991) 431-450.

\item K\'{o}czy, L. and Hirota, K.:
Interpolative Reasoning with Insufficient Evidence in Sparse Fuzzy Rule
Bases,
{\em Information Sciences} 71 (1993) 169-201.

\item Maeda, H., Asaoka, S. and Murakami, S.:
Dynamical Fuzzy Reasoning and Its Application to System Modeling,
{\em Fuzzy Sets and Systems} 80 (1996) 101-109.

\item Marchant, T.:
Cognitive Maps and Fuzzy Implications,
{\em European J. of Operational Research} 114 (1999) 626-637.

\item Mizumoto, M. and Zimmermann, H.-J.:
Comparison of Fuzzy Reasoning Methods,
{\em Fuzzy Sets and Systems} 8 (1982) 253-283.

\item Parsons, S.:
A Proof Theoretic Approach to Qualitative Probabilistic Reasoning,
{\em International Journal of Approximate Reasoning} 19 (1998) 265-297.

\item Raha, S. and Ray, K.S.:
Analogy between Approximate Reasoning and the Method of Interpolation,
{\em Fuzzy Sets and Systems} 51 (1992) 259-266.

\item Raha, S. and Ray, K.S.:
Reasoning with Vague Default,
{\em Fuzzy Sets and Systems} 91 (1997) 327-338.

\item Skala, H.J.:
On Many-Valued Logics, Fuzzy Sets, Fuzzy Logics and Their Applications,
{\em Fuzzy Sets and Systems} 1 (1978) 129-149.

\item Slonim, T.Y. and Schneider, M.:
Design Issues in Fuzzy Case-Based Reasoning,
{\em Fuzzy Sets and Systems} 117 (2001) 251-267.

\item Sugeno, M. and Takagi, T.:
Multi-Dimensional Fuzzy Reasoning,
{\em Fuzzy Sets and Systems} 9 (1983) 313-325.

\item Sun, W. and Davidson, V.J.:
Dynamic Fuzzy-Reasoning-Based Function Estimator,
{\em Fuzzy Sets and Systems} 79 (1996) 357-366.

\item Tsiporkova, E., De Baets, B. and Boeva, V.:
Dempster’s Rule of Conditioning Translated into Modal Logic,
{\em Fuzzy Sets and Systems} 102 (1999) 371-383.

\item Turunen, E.:
Rules of Inference in Fuzzy Sentential Logic,
{\em Fuzzy Sets and Systems} 85 (1997) 63-72.

\item Wang, G.-J.:
On the Logic Foundation of Fuzzy Reasoning,
{\em Information Sciences} 117 (1999) 47-88.

\item Yager, R.R.:
Approximate Reasoning as a Basis for Rule-Based Expert Systems,
{\em IEEE Trans. on Systems, Man, and Cybernetics} 14 (1984) 636-643.

\item Yager, R.R.:
Approximate Reasoning and Conflict Resolution,
{\em International Journal of Approximate Reasoning} 25 (2000) 15-42.

\item Ying, M.:
Perturbation of Fuzy Reasoning,
{\em IEEE Trans. on Fuzzy Systems} 7 (1999) 625-629.

\item Zadeh, L.A. :
The Concept of a Linguistic Variable and Its Application to Approximate
Reasoning – I.
{\em Informatin Sciences} 8 (1975) 199-249.

\item Zadeh, L.A. :
The Concept of a Linguistic Variable and Its Application to Approximate
Reasoning – II.
{\em Informatin Sciences} 8 (1975) 301-357.

\item Zadeh, L.A. :
The Concept of a Linguistic Variable and Its Application to Approximate
Reasoning – III.
{\em Informatin Sciences} 9 (1975) 43-80.

\end{itemize}

\begin{equation}{\label{c}}\tag{C}\mbox{}\end{equation}

Artificial Immune Systems.

\item Bersini, H.:
The Immune and the Chemical Crossover,
{\em IEEE Trans. on Evolutionary Computation} 6 (2002) 306-313.

\item Campelo, F., Guimaraes, F.G., Igarash, H. and Ramirez, J.A.:
A Clonal Selection Algorithm for Optimization in Electromahetics,
{\em IEEE Trans. on Magnetics} 41 (2005) 1736-1739.

\item Cheng, T.-W., Wang, W.-L. and Chen, A.-P.:
E-Marketplace Using Artificial Immune System as Matchmaker,
{\em Proceedings of the IEEE International Conference on E-Commerce
Techonology}, 2004, pp.??.

\item Coello C.C.A. and Cortes, N.C.:
A parallel implementation of an artificial immune system to handle constraints in genetic algorithms: preliminary results,
Proceedings of the IEEE Congress on Evolutionary Computation, 2002, pp.819-824.

\item Coello, C.A.C. and Cort\'{e}s, N.C.:
Solving Multiobjective Optimization Problem Using an Artificial Immune System,
{\em Genetic Programming and Evolvable Machines} 6 (2005) 163-190.

\item Cort\'{e}s, P., Garc\'{i}a, J.M., Munuzuri, J. and Onieva, L.:
Viral Systems: A New Bio-Inspired Optimization Approach,
{\em Computers and Operations Research} 35 (2008) 2840-2860.

\item Cui, X., Li, M. and Fang, T.:
Study of population diversity of multiobjective evolutionary algorithm based
on immune and entropy principles,
Proceedings of the IEEE Congress on Evolutionary Computation, 2001,
pp.1316-1321.

\item de Castro, L.N.:
Immune, Swarm, and Evolutionary Algorithms, Part I: Basic Models,
{\em Proceedings of the 9th International Conference on Neural Information
Processing (2002) 1464-1468.

\item de Castro, L.N. and Von Zuben, F.J.:
Learning and Optimization Using the Colnal Selection Principle,
{\em IEEE Trans. on Evolutionary Computation} 6 (2002) 239-251.

\item Garrett, S.M.:
How Do We Evaluate Artificial Immune Systems?,
{\em Evolutionary Computation} 13 (2005) 145-178.

\item Glickman, M., Balthrop.J. and Forrest, S.:
A Machine Learning Evaluation of an Artificial Immune System,
{\em Evolutionary Computation} 13 (2005) 179-212.

\item Hofmeyr, S.A. and Forrest, S.:
Architecture for an Artificial Immune System,
{\em Evolutionary Computation} 8 (2000) 443-473.

\item Hunt, J.E. and Cooke, D.E.:
Learning Using an Artificial Immune System,
{\em Journal of Network and Computer Applications} 19 (1996) 189-212.

\item Ji, Z. and Dasgupta, D.:
Revisiting Negative Selection Algorithms,
{\em Evolutionary Computation} 15 (2007) 223-251.

\item Karr, C.L., Banerjee, A. and Mishra, P.:
Solving an inverse partial differential equation for a two dimensional heat
conduction problem with oscillating boundary conditions using an artificial immune system,
Proceedings of the IEEE International Conference on Machine Learning and Applications, 2004, pp.99-106.

\item Keko, H., Skok, M. and Skrlec, D.:
Artificial immune systems in solving routing problems,
The IEEE Region 8, EUROCON, Computer as a Tool, 2003, pp.62-66.

\item Kleinstein, S.H. and Seiden, P.E.:
Simulating the Immune System,
{\em Computer Simulations} July/August (2000) 69-77.

\item Li, A., Wang, L., Li, J. and Ji, C.: (Swarm Intelligence)
Application of Immune Algorithm-Based Particle Swarm Optimization for Optimized Load Distribution Among Cascade Hydropower Stations,
{\em Computers and Mathematics with Applications} 57 (2009) 1785-1791.

\item Mori, K., Tsukiyama, M. and Fukuda, T.:
Artificial immunity based management system for a semiconductor production line,
IEEE International Conference on Systems, Man, and Cybernetics, 1997, pp.851-855.

\item Nasaroui, O., Gonzalez, F. and Dasgupta, D.:
The fuzzy artificial immune system: Motivations, basic concepts, and application to clustering and web profiling,
IEEE International Conference on Plasma Science, 2002, pp.711-716.

\item Nohara, B. T. and Takahashi, H.:
Evolutionary computation in Engineering Artificially Immune (EAI) system,
IEEE IECON Proceedings, Industrial Electronics Conference, 2000, pp.2501-2506.

\item Su, M.-C., Yang, Y.-S.,Chou, C.-H., Lai, E. and Hsiao, M.-N.:
An on-line learning neuro-fuzzy system based on artificial immune systems,
Proceedings of the IEEE International Joint Conference on Neural Networks, 2004, pp.1073-1078.

\item Tan, K.C., Goh, C.K., Mamun, A.A. and Ei, E.Z.:
An Evolutionary Artificial Immune System for Multi-Objective Optimization,
{\em European Journal of Operational Research} 187 (2008) 371-392.

\item Tarakanov, A. and Dasgupta, D.:
A Formal Model of an Artificial Immune System,
{\em BioSystems} 55 (2000) 151-158.

\item Timmis, J. and Neal, M.:
A Resource Limited Artificial Immune System for Data Analysis,
{\em Knowledge-Based Systems} 14 (2001) 121-130.

\item Timmis, J., Neal, M. and Hunt, J.:
An Artificial Immune System for Data Analysis,
{\em BioSystems} 55 (2000) 143-150.

\item Watkins, A., Timmis, J. and Boggess, L.:
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm,
{\em Genetic Programming and Evolvable Machines} 5 (2004) 291-317.

\item Zandieh, M., Ghomi, S.M.T.F. and Husseini, S.M.M.:
An Immune Algorithm Approach to Hybrid Flow Shops Scheduling with
Sequence-Dependent Setup Times,
{\em Applied Mathematics and Computation} 180 (2006) 111-127.

\item Zak, M.:
Physical Model of Immune Inspired Computing,
{\em Information Sciences} 129 (2000) 61-79.

\begin{equation}{\label{d}}\tag{D}\mbox{}\end{equation}

Computational Intelligence in Education.

\item Andalord, G. and Bellomonte, L.:
Student Knowledge and Learning Skill Modeling in the Learning
Enviroment Forces,
{\em Computers and Education} 30 (1998) 209-217.

\item Hwang, G.-J., Huang, T.C.K. and Tseng, J.C.R:
A Group-Decision Approach for Evaluating Educational Web Sites,
{\em Computers and Education} 42 (2004) 65-86.

\item Lazzeri, S.G. and Heller, R.:
An Intelligent Consultant System for Chess,
{\em Computers and Education} 27 (1996) 181-196.

\item Ma, J. and Zhou, D.:
Fuzzy Set Approach to the Assessment of Student-Centered Learning,
{\em IEEE Transactions on Education} 43 (2000) 237-241.

\item Yeh, S.-W. and Lo, J.-J.:
Assessing Metacognitive Knowledge in Web-Based CALL: A Neural Network Approach,
{\em Computers and Education} 44 (2005) 97-113.

\begin{equation}{\label{e}}\tag{E}\mbox{}\end{equation}

Random Search.

\item Ali, M.M., Storey, C. and T\”{o}rn, A.: (Random Search)
Application of Stochastic Global Optimization Algorithms to Practical
Problems,
{\em Journal of Optimization Theory and Applications} 95 (1997) 545-563.

\item Barton, R.R. and Ivey, J.S.:
Nelder-Mead Simplex Modifications for Simulation Optimization,
{\em Management Science} 42 (1996) 954-973.

\item Rinnooy Kan, A.H.G. and Timmer, G.T.:
Stochastic Global Optimization Methods, Part I: Clustering Methods,
{\em Mathematical Programming} 39 (1987) 27-56.

\item Rinnooy Kan, A.H.G. and Timmer, G.T.:
Stochastic Global Optimization Methods, Part II: Multi Level Methods,
{\em Mathematical Programming} 39 (1987) 57-78.

\item Solis, F.J. and Wets, R.J.-B.:
Minimization by Random Search Techniques,
{\em Mathematics of Operations Research} 6 (1981) 19-30.

\item T\”{o}rn, A., Ali, M.M. and Viitanen, S.:
Stochastic Global Optimization: Problem Classes and Solution Techniques,
{\em Journal of Global Optimization} 14 (1999) 437-447.

\item Wood, G.R., Alexander, D.L.J. and Bulger, D.W.:
Approximation of the Distribution of Convergence Times for Stochastic
Global Optimization,
{\em Journal of Global Optimization} 22 (2002) 271-284.

\item Ali, M.M. and Storey, C.:
Modified Controlled Random Search Algorithms,
{\em International Journal of Computer Mathematics} 53 (1994) 229-235.

\item Ali, M.M. and T\”{o}rn, A.:
Population Set-Based Global Optimization Algorithms: Some Modifications and
Numerical Studies,
{\em Computers and Operations Research} 31 (2004) 1703-1725.

\item Ali, M.M., T\”{o}rn, A. and Viitanen, S.:
A Numerical Comparison of Some Modified Controlled Random Search Algorithms,
{\em Journal of Global Optimization} 11 (1997) 377-385.

\item Hendrix, E.M.T., Ortigosa, P.M. and Garcia, I.:
On Success Rates for Controlled Random Search,
{\em Journal of Global Optimization} 21 (2001) 239-263.

\item Nelder, J.A. and Mead, R.:
A Simplex Method for Function Minimization,
{\em Computer Journal} 7 (1965) 308-313.

\item Price, W.L.:
A Controlled Random Search Procedure for Global Optimization,
{\em Computer Journal} 20 (1977) 367-370.

\item Price, W.L.:
Global Optimization by Controlled Random Search,
{\em Journal of Optimization Theory and Applications} 40 (1983) 333-348.

\item Price, W.L.:
Global Optimization Algorithms for a CAD Workstation,
{\em Journal of Optimization Theory and Applications} 55 (1987) 133-146.

\begin{equation}{\label{f}}\tag{F}\mbox{}\end{equation}

Differential Evolution.

\item Ali, M.M.:
Differential Evoultion with Preferential Crossover,
{\em European Journal of Operational Research} 181 (2007) 1137-1147.

\item Ali, M.M. and Fatti, L.P.:
A Differential Free Point Generation Scheme in the Differential
Evolution Algorithm,
{\em Journal of Global Optimization} 35 (2006) 551-572.

\item Ali, M.M. and T\”{o}rn, A.:
Population Set-Based Global Optimization Algorithms: Some Modifications and
Numerical Studies,
{\em Computers and Operations Research} 31 (2004) 1703-1725.

\item Kaelo, P. and Ali, M.M.:
A Numerical Study of Some Modified Differential Evolution Algorithms,
{\em European Journal of Operational Research} 169 (2006) 1176-1184.

\item Paterlini, S. and Krink, T.:
Differential Evolution and Particle Swarm Optimization in Partitonal Clustering,
{\em Computational Statistics and Data Analysis} 50 (2006) 1220-1247.

\item Storn, R.:
On the Usage of Differential Evolution for Function Optimization,
{\em IEEE Biennial Conference of the North American, Fuzzy Information
Processing Society}, 1996, 519-523.

\item Storn, R.:
System Design by Constraint Adaptation and Differential Evolution,
{\em IEEE Trans. on Evolutionary Computation} 3 (1999) 22-34.

\item Storn, R. and Price, K.:
Differential Evolution — A Simple and Efficient Heuristic for Global
Optimization over Continuous Spaces,
{\em Journal of Global Optimization} 11 (1997) 341-359.

\begin{equation}{\label{g}}\tag{G}\mbox{}\end{equation}

Fuzzy Control.

\item Abdelnour, G., Cheung, J.Y., Chang, C.-H. and Tinetti, G.:
Application of Describing Functions in the Transient Response Analysis
of a Three-Term Fuzzy Controller,
{\em IEEE Trans. Systems, Man, and Cybernetics} 23 (1993) 603-606.

\item Abdelnour, G., Cheung, J.Y., Chang, C.-H. and Tinetti, G.:
Steady-State Analysis of a Three-Term Fuzzy Controller,
{\em IEEE Trans. Systems, Man, and Cybernetics} 23 (1993) 607-610.

\item Buckley, J.J. \& Ying, H. :
Fuzzy Controller Theory : Limit Theorems for Linear Fuzzy Control Rules,
{\em Automatica} 25 (1989) 469-472.

\item Buckley, J.J. :
Fuzzy I/O Controller,
{\em Fuzzy Sets and Systems} 43 (1991) 127-137.

\item Buckley, J.J. :
Expert Fuzzy Controller,
{\em Fuzzy Sets and Systems} 44 (1991) 373-390.

\item Buckley, J.J. :
Theory of the Fuzzy Controller : An Introduction,
{\em Fuzzy Sets and Systems} 51 (1992) 249-258.

\item Buckley, J.J. :
Controllable Processes and the Fuzzy Controller,
{\em Fuzzy Sets and Systems} 53 (1993) 27-31.

\item Buckley, J.J. :
Sugeno Type Controller are Universal Controllers,
{\em Fuzzy Sets and Systems} 53 (1993) 299-303.

\item Buckley, J.J. :
Stability and Fuzzy Controller,
{\em Fuzzy Sets and Systems} 77 (1996) 167-173.

\item Mamdani, E.H. \& Assilian, S. :
An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller,
{\em Int. J. Man-Machine Studies} 7 (1975) 1-13.

\item Sugeno, M. :
An Introduction Survey of Fuzzy Control,
{\em Information Sciences} 36 (1985) 59-83.

\item Ying, H., Siler, W. \& Buckley, J.J. :
Fuzzy Control Theory : A Nonlinear Case,
{\em Automatica} 26 (1990) 513-520.

\begin{equation}{\label{h}}\tag{H}\mbox{}\end{equation}

Fuzzy Neural Networks.

\item Buckley, J.J. \& Hayashi, Y. :
Numerical Relationships between Neural Networks, Continuous Function, and
Fuzzy Systems,
{\em Fuzzy Sets and Systems} 60 (1993) 1-8.

\item Buckley, J.J. \& Hayashi, Y. :
Hybrid Neural Nets Can be Fuzzy Controllers and Fuzzy Expert Systems,
{\em Fuzzy Sets and Systems} 60 (1993) 135-142.

\item Buckley, J.J. \& Hayashi, Y. :
Can Fuzzy Neural Nets Approximate Continuous Fuzzy Functions ?
{\em Fuzzy Sets and Systems} 61 (1994) 43-52.

\item Buckley, J.J. \& Hayashi, Y. :
Fuzzy Neural Networks : A Survey,
{\em Fuzzy Sets and Systems} 66 (1994) 1-13.

\item Buckley, J.J., Hayashi, Y. \& Czogla, E. :
On the Equivalence of Neural Nets and Fuzzy Expert Systems,
{\em Fuzzy Sets and Systems} 53 (1993) 129-134.

\begin{equation}{\label{i}}\tag{I}\mbox{}\end{equation}

Fuzzy Systems for Approximation.

\item Buckley, J.J. :
Sugeno Type Controller are Universal Controllers,
{\em Fuzzy Sets and Systems} 53 (1993) 299-303.

\item Buckley, J.J.:
Erratum: Universal Fuzzy Controllers,
{\em Automatica} 33 (1997) 1771-1773.

\item Buckley, J.J. and Hayashi, Y. :
Numerical Relationships between Neural Networks, Continuous Function, and
Fuzzy Systems,
{\em Fuzzy Sets and Systems} 60 (1993) 1-8.

\item Buckley, J.J. and Hayashi, Y. :
Can Fuzzy Neural Nets Approximate Continuous Fuzzy Functions ?
{\em Fuzzy Sets and Systems} 61 (1994) 43-52.

\item Buckley, J.J. and Hayashi, Y. :
Can Approximate Reasoning be Consistent ?
{\em Fuzzy Sets and Systems} 65 (1994) 13-18.

\item Castro, J.L.:
Fuzzy Logic Controllers Are Universal Approximators,
{\em IEEE Trans. on Systems, Man, and Cybernetics} 25 (1995) 629-635.

\item Huwendiek, O. and Brockmann, W.:
Function Approximation with Decomposed Fuzzy Systems,
{\em Fuzzy Sets and Systems} 101 (1999) 273-286.

\item K\'{o}czy, L.T. and Zorat, A.:
Fuzzy Systems and Approximation,
{\em Fuzzy Sets and Systems} 85 (1997) 203-222.

\item Wang, L.-X.:
Universal Approximation by Hierarchical Fuzzy Systems,
{\em Fuzzy Sets and Systems} 93 (1998) 223-230.

\item Wang, L.-X. and Mendel, J.M.:
Fuzzy Basis Functions, Universal Approximations, and Orthogonal
Least-Squares Learning,
{\em IEEE Trans. on Neural Networks} 3 (1992) 807-814.

\item Wei, C. and Wang, L.-X.:
A Note on Universal Approximation by Hierarchical Fuzzy Systems,
{\em Information Sciences} 123 (2000) 241-248.

\item Ying, H.:
Sufficient Conditions on General Fuzzy Systems as Function Approximators,
{\em Automatica} 30 (1994) 521-525.

\item Zeng, K., Zhang, N.-Y. and Xu, W.-L.:
A Comparative Study on Sufficient Conditions for Takagi-Sugeno Fuzzy Systems
as Universal Approximators,
{\em IEEE Trans. on Fuzzy Systems} 8 (2000) 773-780.

\begin{equation}{\label{j}}\mbox{J}\end{equation}

Neural Networks for Approximation.

\item Benaim, M.:
On Functional Approximation with Normalized Gausian Units,
{\em Neural Computation} 6 (1994) 319-333.

\item Burton, R.M. and Dehling, H.G.:
Universal Approximation in $p$-Mean by Neural Networks,
{\em Neural Networks} 11 (1998) 661-667.

\item Cardaliaguet, P. and Euvrard, G.:
Approximation of a Function and Its Derivative with a Neural Network,
{\em Neural Networks} 5 (1992) 207-220.

\item Castro, J.L., Mantas, C.J. and Bent\'{i}tez, J.M.:
Neural Networks with a Continuous Squashing Function in the Output are
Universal Approximators,
{\em Neural Networks} 13 (2000) 561563.

\item Chen, T.:
A Unified Approach for Neural Network-Like Approximation of Nonlinear
Functionals,
{\em Neural Networks} 11 (1998) 981-983.

\item Chen, T. and Chen, H.:
Universal Approximation to Nonlinear Operators by Neural Networks with
Arbitrary Activation Functions and Its Application to Dynamical Systems,
{\em IEEE Trans. on Neural Networks} 6 (1995) 911-917.

\item Funahashi, K.-I.:
On the Approximate Realization of Continuous Mappings by Neural Networks,
{\em Neural Networks} 2 (1989) 183-192.

\item Geva, S. and Sitte, J.:
A Constructive Method for Multivariate Function Approximation by
Multilayer Perceptrons,
{\em IEEE Trans. on Neural Networks} 3 (1992) 621-624.

\item Hartman, E.J., Keeler, J.D. and Kowalski, J.M.:
Layered Neural Networks with Gaussian Hidden Units as Universal
Approximations,
{\em Neural Computation} 2 (1990) 210-215.

\item Hornik, K.:
Approximation Capabilities of Multilayer Feedforward Netwroks,
{\em Neural Networks} 4 (1991) 251-257.

\item Hornik, K.:
Some New Results on Neural Network Approximation,
{\em Neural Networks} 6 (1993) 1069-1072.

\item Hornik, K., Stinchcombe, M. and White, H.:
Universal Approximation of an Unknown Mapping and Its Derivatives Using
Multilayer Feedforward Networks,
{\em Neural Networks} 3 (1990) 551-560.

\item Hornik, K., Stinchcombe, M. and White, H.:
Multilayer Feedforward Networks are Universal Approximators,
{\em Neural Networks} 2 (1989) 359-366.

\item Ito, Y.:
Approximation of Functions on a Compact Set by Finite Sums of a Sigmoid
Without Scaling,
{\em Neural Networks} 4 (1991) 817-826.

\item Ito, Y.:
Approximation of Continuous Functions on ${\bf R}^{d}$ by Linear
Combinations of Shifted Rotations of a Sigmoid Function With and
Without Scaling,
{\em Neural Networks} 5 (1992) 105-115.

\item Kreinovich, V.Y.:
Arbitrary Nonlinearity Is Sufficient to Represent All Functions by Neural
Networks: A Theorem,
{\em Neural Networks} 4 (1991) 381-383.

\item K\.{u}rkov\'{a}, V.:
Kolmogorov’s Theorem Is Relevant,
{\em Neural Computation} 3 (1991) 617-622.

\item K\.{u}rkov\'{a}, V.:
Kolmogorov’s Theorem and Multilayer Neural Networks,
{\em Neural Networks} 5 (1992) 501-506.

\item Leonard, J.A., Kramer, M.A. and Ungar, L.H.:
Using Radial Basis Functions to Approximate a Function and Its Error
Bounds,
{\em IEEE Trans. on Neural Networks} 3 (1992) 624-627.

\item Maiorov, V. and Pinkus, A.:
Lower Bounds for Approximation by MLP Neural Networks,
{\em Neurocomputing} 25 (1999) 81-91.

\item Park, J. and Sandberg, I.W.:
Universal Approximation Using Radial-Basis-Function Networks,
{\em Neural Computation} 3 (1991) 246-257.

\item Poggio, T. and Girosi, F.:
Networks for Approximation and Learning,
{\em Proceedings of the IEEE} 78 (1990) 1481-1497.

\item Ruzinsky, S.A. and Olsen, E.T.:
$L_{1}$ and $L_{\infty}$ Minimization via a Variant of Karmarkar’s Algorithm,
{\em IEEE Trans. on Acoustic, Speech, and Signal Proceesing} 37 (1989)
245-253.

\item Scarselli, F. and Tsoi, A.C.:
Universal Approximation Using Feedforward Neural Networks: A Survey of Some
Existing Methods, and Some New Results,
{\em Neural Networks} 11 (1998) 15-37.

\item Siu, K.-Y., Roychowdhury, V.P. and Kailath, T.:
Rational Approximation Techniques for Analysis of Neural Networks,
{\em IEEE Trans. on Information Theory} 40 (1994) 455-466.

\item Stein, D. and Feuer, A.:
Cubic Approximation Neural Network for Multivariate Functions,
{\em Neural Networks} 11 (1998) 235-248.

\item Stinchcombe, M.B.:
Neural Network Approximation of Continuous Functions and Continuous
Functions on Compactifications,
{\em Neural Networks} 12 (1999) 467-477.

\item Suzuki, S.:
Constructive Function-Approximation by Three-Layer Artificial Neural Networks,
{\em Neural Networks} 11 (1998) 1049-1058.

\item Vecci, L., Piazza, F. and Uncini, A.:
Learning and Approximation Capabilities of Adaptive Spline Activation
Function Neural Networks,
{\em Neural Networks} 11 (1998) 259-270.

\begin{equation}{\label{k}}\tag{K}\mbox{}\end{equation}

Generating Fuzzy Rules.

\begin{enumerate}

\item Abe, S. and Lan, M.-S.:
A Method for Fuzzy Rules Extraction Directly from Numerical Data and Its
Application to Pattern Classification,
{\em IEEE Trans. on Fuzzy Systems} 3 (1995) 18-28.

\item Abe, S. and Lan, M.-S.:
Fuzzy Rules Extraction Directly from Numerical Data for Function
Approximation,
{\em IEEE Trans. on Systems, Man, and Cybernetics} 25 (1995) 119-129.

\item Finn, G.D.:
Learning Fuzzy Rules from Data,
{\em Neural Computing and Applications} 8 (1999) 9-24.

\item Huang, S.H. and Xing, H.:
Extract Intelligible and Concise Fuzzy Rules from Neural Networks,
{\em Fuzzy Sets and Systems} 132 (2002) 233-243.

\item Mitra, S. and Pal, S.K.:
Logical Operation Based Fuzzy MLP for Classification and Rule Generation,
{\em Neural Networks} 7 (1994) 353-373.

\item Nozaki, K., Ishibuchi, H. and Tanaka, H.:
A Simple but Powerful Heuristic Method for Generating Fuzzy Rules from
Numerical Data,
{\em Fuzzy Sets and Systems} 86 (1997) 251-270.

\item Setnes, M.:
Supervised Fuzzy Clustering for Rule Extraction,
{\em IEEE Trans. on Fuzzy Systems} 8 (2000) 416-424.

\item Wang, L.-X. and Mendel, J.M.:
Generating Fuzzy Rules by Learning from Examples,
{\em IEEE Trans on Systems, Man, and Cybernetics} 22 (1992) 1414-1427.

\item Wong, C.-C. and Lin, N.-S.:
Rule Extraction for Fuzzy Modeling,
{\em Fuzzy Sets and Systems} 88 (1997) 23-30.

\begin{equation}{\label{l}}\tag{L}\mbox{}\end{equation}

Genetic Fuzzy Systems.

\item Abbod, M.F., Mahfouf, M. and Linkens, D.A.:
Multi-Objective Genetic Optimization for Self-Organizing Fuzzy Logic Control,
{\em UKACC International Conference on Control}, 1998, 1575-1580.

\item Bastian, A.:
Identifying Fuzzy Models Utilizing Genetic Programming,
{\em Fuzzy Sets and Systems} 113 (2000) 333-350.

\item Buckley, J.J. \& Hayashi, Y. :
Fuzzy Genetic Algorithm and Applications,
{\em Fuzzy Sets and Systems} 61 (1994) 129-136.

\item Caponetto, R., LoPresti, M. and Vinci, C.:
Genetic Optimization for the Design of an n-Step Fuzzy Controller,
{\em IEEE International Conference on Systems, Man, and Cybernetics}, 1995,
849-851.

\item Casillas, J., Cordon, O., del Jesus, M.J. and Herrera, F.:
Genetic Tuning of Fuzzy Rule Deep Structures Preserving Interpretability
and Its Interaction with Fuzzy Rule Set Reduction,
{\em IEEE Transactions on Fuzzy Systems} 13 (2005) 13-29.

\item Chan, K.C.C., Lee, V. and Leung, H.:
Generating Fuzzy Rules for Target Tracking Using a Steady-State Genetic
Algorithm,
{\em IEEE Trans. on Evolutionary Computation} 1 (1997) 189-200.

\item Chan, P.T., Xie, W.F. and Rad, A.B.:
Tuning of Fuzzy Controller for an Open-Loop Unstable System: A Genetic
Approach,
{\em Fuzzy Sets and Systems} 111 (2000) 137-152.

\item Chin, T.C. and Qi, X.M.:
Genetic Algorithms for Learning the Rule Base of Fuzzy Logic Controller,
{\em Fuzzy Sets and Systems} 97 (1998) 1-7.

\item Cho, H.-J., Cho, K.-B. and Wang, B.-H.:
Fuzzy-PID Hybrid Control: Automatic Rule Generation Using Genetic
Algorithms,
{\em Fuzzy Sets and Systems} 92 (1991) 305-316.

\item Cho, H.-J., Wang, B.-H. and Roychowdhury, S.:
Automatic Rule Generation for Fuzzy Controllers Using Genetic Algorithms:
A Study on Representation Scheme and Mutation Rate,
{\em IEEE International Conference on Fuzzy Systems}, 1998, 1290-1295.

\item Cord\'{o}n, O. and Herrera, F.:
A Three-Stage Evolutionary Process for Learning Descriptive and
Approximate Fuzzy-Logic-Controller Knowledge Bases from Examples,
{\em International Journal of Approximate Reasoning} 17 (1997) 369-407.

\item Fagarasan, F.:
A Genetic-Based Method Applied in Fuzzy Modeling,
{\em IEEE International Conference on Evolutionary Computation}, 1996,
253-257.

\item Fathi-Torbaghan, M. and Hildebrand, L.:
The Application of Evolutionary Strategies to the Problem of Parameter
Optimization in Fuzzy Rule-Based Systems,
{\em IEEE International Conference on Evolutionary Computation}, 1995.

\item Gonzalez, A. and P\'{e}rez, R.:
Completeness and Consistency Conditions for Learning Fuzzy Rules,
{\em Fuzzy Sets and Systems} 96 (1998) 37-51.

\item Heider, H. and Drabe, T.:
A Cascade Genetic Algorithm for Improving Fuzzy-System Design,
{\em International Journal of Approximate Reasoning} 17 (1997) 351-368.

\item Homaifar, A. and McCormick, E.:
Simultaneous Design of Membership Functions and Rule Sets for Fuzzy
Controllers Using Genetic Algorithms,
{\em IEEE Trans. on Fuzzy Systems} 3 (1995) 129-139.

\item Huang, Y.-P. and Huang, C.-H.:
Real-Valued Genetic Algorithms for Fuzzy Grey Prediction System,
{\em Fuzzy Sets and Systems} 87 (1997) 265-276.

\item Huang, Y.-P. and Wang, S.-F.:
Identifying the Fuzzy Grey Prediction Model by Genetic Algorithms,
{\em IEEE International Conference on Evolutionary Computation}, 1996,
720-725.

\item Huang, Y.-P. and Wang, S.-F.:
The Identification of Fuzzy Grey Prediction Systen by Genetic Algorithms,
{\em International Journal of Systems Science} 28 (1997) 15-24.

\item Ishibuchi, H., Murata, T. and T\”{u}rksen, I.B.:
Single-Objective and Two-Objective Genetic Algorithms for Selecting
Linguistic Rules for Pattern Classification Problems,
{\em Fuzzy Sets and Systems} 89 (1997) 135-150.

\item Ishibuchi, H., Nozaki, K. and Yamamoto, N.:
Selecting Fuzzy Rules by Genetic Algorithm for Classification Problems,
{\em IEEE Internatinal Conference on Fuzzy Systems}, 1993, 1119-1124.

\item Ishibuchi, H., Nozaki, K., Yamamoto, N. and Tanaka, H.:
Construction of Fuzzy Classification Systems with Rectangular Fuzzy Rules
Using Genetic Algorithms,
{\em Fuzzy Sets and Systems} 65 (1994) 237-253.

\item Ishibuchi, H., Nozaki, K., Yamamoto, N. and Tanaka, H.:
Selecting Fuzzy If-Then Rules for Classification Problems Using Genetic
Algorithms,
{\em IEEE Trans. on Fuzzy Systems} 3 (1995) 260-270.

\item Joo, Y.H., Hwang, H.S., Kim, K.B. and Woo, K.B.:
Fuzzy System Modeling by Fuzzy Partition and GA Hybrid Schemes,
{\em Fuzzy Sets and Systems} 86 (1997) 279-288.

\item Karr, C.:
Genetic Algorithms for Fuzzy Controllers,
{\em AI Expert} February (1991) 26-33.

\item Karr, C.:
Applying Genetics to Fuzzy Logic,
{\em AI Expert} March (1991) 38-43.

\item Karr, C.L. and Gentry, E.J.:
Fuzzy Control of pH Using Genetic Algorithms,
{\em IEEE Trans. on Fuzzy Systems} 1 (1993) 46-53.

\item Kim, D. and Lee, H.-P.:
An Optimal Design of Neuro-FLC by Lamarckian Co-adaptation of Learning and
Evolution,
{\em Fuzzy Sets and Systems} 118 (2001) 319-337.

\item Kim, J., Moon, Y. and Zeigler, B.P.:
Designing Fuzzy Net Controllers Using GA Optimization,
{\em IEEE/IFAC Joint Symposium on Compuetr-Aided Control System Design},
1994, 83-88.

\item Kim, J., Moon, Y. and Zeigler, B.P.:
Designing Fuzzy Net Controllers Using Genetic Algorithms,
{\em IEEE Control Systems Magazine} June, 1995, 66-72.

\item Lekova, A., Mikhailov, L., Boyadjiev, D. and Nabout, A.:
Redundant Fuzzy Rules Exclusion by Genetic Algorithms,
{\em Fuzzy Sets and Systems} 100 (1998) 235-243.

\item Li, T.-H. S. and Shieh, M.-Y.:
Design of a GA-Based Fuzzy PID Controller for Non-minimum Phase Systems,
{\em Fuzzy Sets and Systems} 111 (2000) 183-197.

\item Liu, J. and Lampinen, J.:
A Fuzzy Adaptive Differential Evolution Algorithm,
{\em Soft Computing} 9 (2005) 448-462.

\item Lin, S.-C. and Chen, Y.-Y.:
Design of Self-Learning Fuzzy Sliding Mode Controllers Based on Genetic
Algorithms,
{\em Fuzzy Sets and Systems} 86 (1997) 139-153.

\item Lim, M.H., Rahardja, S. and Gwee, B.H.:
A GA Paradigm for Learning Fuzzy Rules,
{\em Fuzzy Sets and Systems} 82 (1996) 177-186.

\item Linkens, D.A. and Nyongesa, H.O.:
A Distributed Genetic Algorithm for Multivariable Fuzzy Control,
{\em IEE Colloquium on Genetic Algorithms for Control Systems Engineering},
1993, 9/1-9/3.

\item Linkens, D.A. and Nyongesa, H.O.:
Learning Systems in Intelligent Control: An Apprasial of Fuzzy, Neural and
Genetic Algorithm Control Applications,
{\em IEE-Proc. Control Theory Appl.} 143 (1996) 367-386.

\item Magdalena, L.:
Adapting the Gain of an FLC with Genetic Algorithms,
{\em International Journal of Approximate Reasoning} 17 (1997) 327-349.

\item Magdalena, L. and Monasterio, F.:
Evolutionary-Based Learning Applied to Fuzzy Controllers,
{\em IEEE International Conference on Fuzzy Systems}, 1995, 1111-1118.

\item Matsushita, S., Furuhashi, T., Tsutsui, H. and Uchikawa, Y.:
Efficient Search for Fuzzy Models Using Genetic Algorithm
{\em Information Sciences} 110 (1998) 41-50.

\item Nawa, N.E. and Furuhashi, T.:
Bacterial Evolutionary Algorithm for Fuzzy System Design,
{\em IEEE International Conference on Systems, Man, and Cynebrnetics}, 1998,
2424-2429.

\item Nawa, N.E. and Furuhashi, T.:
Fuzzy System Parameters Discovery by Bacterial Evolutionary Algorithm,
{\em IEEE Trans. on Fuzzy Systems} 7 (1999) 608-616.

\item Negoita, M.G., Giuclea, M. and Dediu, H.:
GA to Optimize Approximate Solutions of Fuzzy Relational Equation for
Fuzzy Systems or Controllers,
{\em IEEE Second New Zealand International Two-Stream Conference on
Artificial Neural Networks and Expert Systems}, 1995, 124-127.

\item Nelles, O., Fischer, M. and M\”{u}ller, B.:
Fuzzy Rule Extraction by a Genetic Algorithm and Constrained Nonlinear
Optimization of Membership Functions,
{\em IEEE International Conference on Fuzzy Systems}, 1996, 213-219.

\item \”{O}stermark, R.:
A Neuro-Genetic Algorithm for Heteroskedastic Time-Series Processes
Empirical Tests on Global Asset Returns,
{\em Soft Computing} 3 (1999) 206-220.

\item Park, D., Kandel, A. and Langholz, G.:
Genetic-Based New Fuzzy Reasoning Models with Application to Fuzzy Control,
{\em IEEE Trans. on Systems, Man, and Cybernetics} 24 (1994) 39-47.

\item Park, Y.J., Cho, H.S. and Cha, D.H.:
Genetic Algorithms-Based Optimization of Fuzzy Logic Controller Using
Characteristic Parameters,
{\em IEEE International Conference on Evolutionary Computation}, 1995.

\item Pavel, O. and Radomil, M.:
Automatic Optimal Design of Fuzzy Controllers Based on Genetic Algorithms,
{\em Internationa Conference Genetic Algorithms in Engineering Systems:
Innovations and Applications}, 1997, 439-443.

\item Perneel, C., Themlin, J.-M., Renders, J.-M. and Acheroy, M.:
Optimization of Fuzzy Expert Systems Using Genetic Algorithms and Neural
Networks,
{\em IEEE Trans. on Fuzzy Systems} 3 (1995) 300-312.

\item Perrot, N., \'{M}e, L., Trystram, G., Trichard, J.-M. and Decloux, M.:
Optimal Control of the Microfiltration of Sugar Produce Using a Controller
Combining Fuzzy and Genetic Approaches,
{\em Fuzzy Sets and Systems} 94 (1998) 309-322.

\item Ray, K.S. and Ghoshal, J.:
Neuro-Genetic Approach to Multidimensional Fuzzy Reasoning for Pattern
Classification,
{\em Fuzzy Sets and Systems} 112 (2000) 449-483.

\item Rojas, I., Merelo, J.J., Bernier, J.L. and Prieto, A.:
A New Approach to Fuzzy Controller Designing and Conding via Genetic
Algorithms,
{\em IEEE International Conference on Fuzzy Systems}, 1997, 1505-1510.

\item Russo, M.:
Genetic Fuzzy Learning,
{\em IEEE Trans. on Evolutionary Computation} 4 (2000) 259-273.

\item Setnes, M. and Roubos, H.:
GA-Fuzzy Modeling and Classification: Complexity and Performance,
{\em IEEE Trans. on Fuzzy Systems} 8 (2000) 509-522.

\item Shi, Y., Eberhart, R. and Chen, Y.:
Implementation of Evolutionary Fuzzy Systems,
{\em IEEE Trans. on Fuzzy Systems} 7 (1999) 109-119.

\item Soodamani, R. and Liu, Z.Q.:
GA-Based Learning for a Model-Based Object Recognition System,
{\em International Journal of Approximate Reasoning} 23 (2000) 85-109.

\item Tanaka, M., Ye, J. and Tanino, T.:
Fuzzy MOdelling by Genetic Algorithm with Tree-Structured Individals,
{\em Int. J. Systems Science} 27 (1996) 261-268.

\item Tsang, E.C.C., Yeung, D.S. and Lee, J.W.T.:
Refinement of Knowledge Representation Parameters in Fuzzy Production Rules
by Genetic Algorithms,
{\em IEEE International Conference on Systems, Man, and Cynebrnetics}, 1998,
1518-1523.

\item Var\v{s}ek, A., Urban\v{c}i\c{c}, T. and Filipi\v{c}, B.:
Genetic Algorithms in COntroller Design and Tuning,
{\em IEEE Trans. on Systems, Man, and Cybernetics} 23 (1993) 1330-1339.

\item Wang, L. and Yen, J.:
Extracting Fuzzy Rules for System Modeling Using a Hybrid of Genetic
Algorithms and Kalman Filter,
{\em Fuzzy Sets and Systems} 101 (1999) 353-362.

\item Wang, P.Y., Wang, G.S., Somg, Y.H. and Johns, A.T.:
Fuzzy Logic Controlled Genetic Algorithms,
{\em IEEE International Conference on Fuzzy Systems}, 1996, 972-979.

\item Wong, C.-C. and Feng, S.-M.:
Switching-Type Fuzzy Controller Design by Genetic Algorithms,
{\em Fuzzy Sets and Systems} 74 (1995) 175-185.

\item Wong, C.-C. and Her, S.-M.:
A Self-Generating Method for Fuzzy System Design,
{\em Fuzzy Sets and Systems} 103 (1999) 13-25.

\item Xu, H.Y. and Vukovich, G.:
A Fuzzy Genetic Algorithm with Effective Search and Optimization,
{\em International Joint Conference on Neural Networks}, 1993, 2967-2970.

item Yi, J., Yan, H., Sun, H. and Hou, Y.:
Fuzzy Control Technique Based on Genetic Algorithms Optimizing and Its
Applications,
{\em IEEE International Conference on Intelligent Processing Systems}, 1997,
329-333.

\item Yu, J., Ye, Z. and Guo, C.:
Using Genetic Algorithms in Fine-Tuning of Fuzzy Logic Controller,
{\em IEEE International Conference on Intelligent Processing Systems}, 1997, 597-601.

\item Yuan, Y. and Zhuang, H.:
A Genetic Algorithm for Generating Fuzzy Classification Rules,
{\em Fuzzy Sets and Systems} 84 (1996) 1-19.

\item Zhang, Y., Chen, W., Xu, B. and Fang, C.:
Application of Domain Evolution Model-Based Genetic Algorithm with Fuzzy Environment Factor to System Optimization,
{\em IEEE International Conference on Systems, Man, and Cybernetics}, 1996, 1936-1941.

\item Zhou, Y.-S. and Lai, L.-Y.:
Optimal Design for Fuzzy Controllers by Genetic Algorithms,
{\em IEEE International Conference on Industrial Automation and Control}, 1995, 429-435.

\item Antonsson, E.K. and Sebastian, H.-J.:
Fuzzy Fitness Functions Applied to Engineering Design Problems,
{\em European Journal of Operational Research} 166 (2005) 794-811.

\iten Van Hove, H. and Verschoren, A.:
A Fuzzy Schema Theorem,
{\em Fuzzy Sets and Systems} 94 (1998) 93-99.

\item Verdegay, J.L., Yager, R.R. and Bonissone, P.P.:
On Heuristics as a Fundamental Consituent of Soft Computing,
{\em Fuzzy Sets and Systems} 159 (2008) 846-855.

\item Voget, S. and Kolonko, M.:
Multidimensional Optimization with a Fuzzy Genetic Algorithm,
{\em Journal of Heuristics} 4 (1998) 221-244.

\begin{equation}{\label{m}}\tag{M}\mbox{}\end{equation}

Neural Networks for Time Series.

\item Billings, S.A. and Hong, X.:
Dual-Orthogonal Radial Basis Function Networks for Nonlinear Time Series
Prediction,
{\em Neural Networks} 11 (1998) 479-493.

\item Chakraborty, K., Mehrotra, K., Mohan, C. and Ranka, S.:
Forecasting the Behavior of Multivariate Time Series Using Neural Networks,
{\em Neural Networks} 5 (1992) 961-970.

\item Ciocoiu, I.B.:
Time Series Analysis Using RBF Networks with FIR/IIR Synapses,
{\em Neurocomputing} 20 (1998) 57-66.

\item Hartman, E. and Keeler, J.D.:
Predicting the Future: Advantages of Semilocal Units,
{\em Neural Computation} 3 (1991) 566-578.

\item Ishikawa, M. and Moriyama, T.:
Prediction of Time Series by a Structural Learning of Neural Networks,
{\em Fuzzy Sets and Systems} 82 (1996) 167-176.

\item L\'{o}pez, V., Huerta, R. and Dorronsoro, J.R.:
Recurrent and Feedforward Polynomial Modeling of Coupled Time Series,
{\em Neural Computation} 5 (1993) 795-811.

\item Maguire, L.P., Roche, B., McGinnity, T.M. and McDaid, L.J.:
Predicting a Chaotic Time Series Using a Fuzzy Neural Network,
{\em Information Sciences} 112 (1998) 125-136.

\item Nie, J.:
Nonlinear Time-Series Forcasting: A Fuzzy-Neural Approach,
{\em Neurocomputing} 16 (1997) 63-76.

\item Refenes, A.N., Bentz, Y., Bunn, D.W., Burgess, A.N. and Zapranis, A.D.:
Financial Time Series Modelling with Discounted Least Squares Backpropogation,
{\em Neurocomputing} 14 (1997) 123-138.

\item Schmitz, G.P.J. and Aldrich, C.:
Combinatorial Evolution of Regression Nodes in Feedforward Neural Networks,
{\em Neural Networks} 12 (1999) 175-189.

\item Specht, D.F.:
A General Regression Neural Network,
{\em IEEE Trans. on Neural Networks} 2 (1991) 568-576.

\item White, H.:
Connectionist Nonparametric Regression: Multilayer Feedforward Networks
Can Learn Arbitrary Mappings,
{\em Neural Networks} 3 (1990) 535-549.

\begin{equation}{\label{n}}\tag{N}\mbox{}\end{equation}

Rough Sets.

\item Beaubouef, T., Petry, F.E. and Arora, G.:
Information-Theoretic Measures of Uncertainty for Rough Sets and Rough
Relational Databases,
{\em Information Sciences} 109 (1998) 185-195.

\item Bonikowski, Z., Bryniarski, E. and Wybraniec-Skardowska, U.:
Extensions and Intensions in the Rough Set Theory,
{\em Information Sciences} 107 (1998) 149-167.

\item Chakraborty, K., Biswas, R. and Nanda, S.:
Fuzziness in Rough Sets,
{\em Fuzzy Sets and Systems} 110 (2000) 247-251.

\item Chan, C.-C.:
A Rough Set Approach to Attribute Generalization in Data Mining,
{\em Information Sciences} 107 (1998) 169-176.

\item Chanas, S. and Kuchta, D.:
Further Remarks on the Relation between Rough and Fuzzy Sets,
{\em Fuzzy Sets and Systems} 47 (1992) 391-394.

\item Dimitras, A.I., Slowinski, R., Susmaga, R. and Zopounidis, C.:
Business Failure Prediction Using Rough Sets,
{\em European Journal of Operational Research} 114 (1999) 263-280.

\item Gorzalczany, M.B. and Piasta, Z.:
Neuro-Fuzzy Approach versus Rough-Set Inspired Methodology for Intelligent
Decision Support,
{\em Information Sciences} 120 (1999) 45-68.

\item Greco, S., Matarazzo, B. and Slowinski, R.:
Rough Approximation of a Preference Relation by Dominance Relations,
{\em European Journal of Operational Research} 117 (1999) 63-83.

\item Kryszkiewicz, M.: (Rough Sets)
Rough Set Approach to Incomplete Information Systems,
{\em Information Sciences} 112 (1998) 39-49.

\item Morsi, N.N. and Yakout, M.M.:
Aximatics for Fuzzy Rough Sets,
{\em Fuzzy Sets and Systems} 100 (1998) 327-342.

\item Quafafou, M.:
$\alpha$-RST: A Generalization fo Rough Set Theory,
{\em Information Sciences} 124 (2000) 301-316.

\item Radzikowska, A.M. and Kerre, E.E.:
A Comparative Study of Fuzzy Rough Sets,
{\em Fuzzy Sets and Systems} 126 (2002) 137-155.

\item Rebolledo, M.:
Rough Intervals — Enhancing Intervals for Qualitative Modeling of Technical Systems,
{\em Artificial Intelligence} 170 (2006) 667-685.

\item Salonen, H. and Nurmi, H.:
A Note on Rough Sets and Common Knowledge Events,
{\em European Journal of Operational Research} 112 (1999) 692-695.

\item Slowinski, R. and Vanderpooten, D.:
A Generalized Definition of Rough Approximation Based on Similarity,
{\em IEEE Trans. on KNowledge and Data Engineering} 12 (2000) 331-336.

\item Yao, Y.Y.: (Rough Sets)
Two Views of the Theory of Rough Sets in Finite Universe,
{\em International Journal of Approximate Reasoning} 15 (1996) 291-317.

\item Yao, Y.Y.:
Constructive and Algebraic Methods of the Theory of Rough Sets,
{\em Information Sciences} 109 (1998) 21-47.

\item Yao, Y.Y.:
A Comparative Study of Fuzzy Sets and Rough Sets,
{\em Information Sciences} 109 (1998) 227-242.

\item Yao, Y.Y.:
Relational Interpretations of Neighborhood Operators and Rough Set
Approximation Operators,
{\em Information Sciences} 111 (1998) 239-259.

\begin{equation}{\label{o}}\tag{O}\mbox{}\end{equation}

Scatter Search.

\item Adenso-D\'{i}az, B., Garc\'{i}a-Carbajal, S. and Lozano, S.:
An Empirical Investigation on Parallelization Strategies for Scatter
Search,
{\em European Journal of Operational Research} 169 (2006) 490-507.

\item Beausoleil, R.P.:
“MOSS” Multiobjective Scatter Search Applied to Nonlinear Multiple
Criteria Optimization,
{\em European Journal of Operational Research} 169 (2006) 426-449.

\item Campos, V., Glover, F., Laguna, M. and Marti, R.:
An Experimental Evaluation of a Scatter Search for the Linear Ordering
Problem,
{\em Journal of Global Optimization} 21 (2001) 397-414.

\item da Silva, C.G., Cl\'{i}maco, J. and Figueria, J.:
A Scatter Search Method for Bi-Criteria $\{0,1\}$-Knapsack Problems,
{\em European Journal of Operational Research} 169 (2006) 373-391.

\item Debels, D., de Reyck, B., Leus, R. and Vanhoucke, M.:
A Hybrid Scatter Search/Electromagnetism Meta-Heuristic for Project
Scheduling,
{\em European Journal of Operational Research} 169 (2006) 638-653.

\item Gonz\'{a};ez, B. and Adenso-D\'{i}az, B.:
A Scatter Search Approach to the Optimum Disassembly Sequence Problem,
{\em Computers and Operations Research} 33 (2006) 1776-1793.

\item Herrera, F., Lozano, M. and Molina, D.:
Continuous Scatter Search: An Analysis of the Integration of Some
Combination Methods and Improvement Strategies,
{\em European Journal of Operational Research} 169 (2006) 450-476.

\item L\'{o}pez, F.G., Torres, M.G., Batista, B.M., P\'{e}rez, J.A.M.
and Moreno-Vega, J.M.:
Solving Feature Subset Selection Problem by a Parallel Scatter Search,
{\em European Journal of Operational Research} 169 (2006) 477-489.

\item Mart\'{i}, R., Laguna, M. and Glover, F.:
Principles of Scatter Search,
{\em European Journal of Operational Research} 169 (2006) 359-372.

\item Nowicki, E. and Smutnicki, C.:
Some Aspects of Scatter Search in the Flow-Shop Problem,
{\em European Journal of Operational Research} 169 (2006) 654-666.

\item Pinol, H. and Beasley, J.E.:
Scatter Search and Bionomic Algorithms for the Aircraft Landing Problem,
{\em European Journal of Operational Research} 171 (2006) 439-462.

\item Yamashita, D.S., Armentano, V.A. and Laguna, M.:
Scatter Search for Project Scheduling with Resource Availability Cost,
{\em European Journal of Operational Research} 169 (2006) 623-637.

\begin{equation}{\label{p}}\tag{P}\mbox{}\end{equation}

Simulated Annealing.

\item Aarts, E.H.L., de Bont, F.M.J., Habers, E.H.A. and
van Laarhoven, P.J.M.:
Parallel Implementations of the Statistical Cooling Algorithm,
{\em Integration, the VLSI Journal} 4 (1986) 209-238.

\item Aarts, E.H.L., Korst, J.H.M. and van Laarhoven, P.J.M.:
A Quantitative Analysis of the Simulated Annealing Algorithm: A Case
Study for the Travelling Salesman Problem,
{\em Journal of Statistical Physics} 50 (1988) 187-206.

\item Aarts, E.H.L. and Van Laarhoven, P.J.M.:
Statistical Cooling: A General Approach to Combinatorial Optimization
Problems,
{\em Philips J. Research} 40 (1985) 193-226.

\item Ali, M.M. and Storey, C.:
Aspiration Based Simulated Annealing Algorithm,
{\em Journal of Global Optimization} 11 (1997) 181-191.

\item Alkhamis, T.M., Hasan, M. and Ahmed, M.A.:
Simulated Annealing for the Unconstrained Quadratic Pseudo-Boolean Function,
{\em European Journal of Operational Research} 108 (1998) 641-652.

\item Angelis, L., Bora-Senta, E. and Moyssiadis, C.:
Optimal Exact Experimental Designs with Correlated Errors through a
Simulated Annealing Algorithm,
{\em Computational Statistics and Data Analysis} 37 (2001) 275-296.

\item Anily, S.:
Simulated Annealing Methods with General Acceptance Probabilities,
{\em Journal of Applied Probability} 24 (1987) 657-667.

\item Anily, S. and Federgruen, A.:
Simulated Annealing Methods with General Acceptance Probabilities,
{\em J. Applied Probability} 24 (1987) 657-667.

\item Anily, S. and Federgruen, A.:
Ergodicity in Parametric Nonstationary Markov Chains: An Application to
Simulated Annealing Methods,
{\em Operations Research} 35 (1987) 867-874.

\item Aydin, M.E. and Fogarty, T.C.:
A Distributed Evolutionary Simulated Annealing for Combinatorial
Optimization Problems,
{\em Journal of Heuristics} 10 (2004) 269-292.

\item Azizi, N. and Zolfaghari, S.:
Adaptive Temparature Control for Simulated Annealing: A Comparative Study,
{\em Computers and Operations Research} 31 (2004) 2439-2451.

\item Baykasoglu, A.:
Preemptive Goal Programming Using Simulated Annealing,
{\em Engineering Optimization} 37 (2005) 49-63.

\item Bilbro, G.L. and Snyder, W.E.:
Optimization of Functions with Many Minima,
{\em IEEE Trans. Systems, Man and Cybernetics} 21 (1991) 840-849.

\item Bohachevsky, I.O., Johnson, M.E. and Stein, M.L.:
Generalized Simulated Annealing for Function Optimization,
{\em Technometrics} 28 (1986) 209-217.

\item Bonomi, E. and Lutton, J.-L.:
The Asymptotic Behaviour of Quadratic Sum Assignment Problems: A
Statistical Mechanics Approach,
{\em European Journal of Operational Research} 26 (1986) 295-300.

\item Bounds, D.G.:
A Statistical Mechanical Study of Boltzmann Machines,
{\em Journal of Physics A}: Math. Gen. 20 (1987) 2133-2145.

\item Carnevali, P., Coletti, L. and Patarnello, S.:
Image Processing by Somulated Annealing,
{\em IBM Journal of Research and Development} 29 (1985) 569-579.

\item Casotto, A., Romeo, F. and Sangiovanni-Vincentelli, A.:
A Parallel Simulated Annealing Algorithm for the Placement of Macro-Cells,
{\em IEEE Trans. on Computer-Aided Design} 5 (1987) 838-847.

\item Catoni, O.:
The Energy Transformation Method for the Metropolis Algorithm Compated
with Simulated Annealing,
{\em Probability Theory and Related Fields} 110 (1998) 69-89.

\item Catthoor, F., de Man, H. and Vandewalle, J.:
SAMURAI: A General and Efficient Simulated-Annealing Schedule with Fully
Adaptive Annealing Parameters,
{\em Integration, the VLSI Journal} 6 (1988) 147-178.

\item Chams, M., Hertz, A. and de Werra, D.:
Some Experiments with Simulated Annealing for Coloring Graphs,
{\em European Journal of Operational Research} 32 (1987) 260-266.

\item Connolly, D.:
General Purpose Simulated Annealing,
{\em Journal of the Operational Research Society} 43 (1992) 495-505.

\item Corana, A., Marchesi, M., Martini, C. and Ridella, S.:
Minimizing Multimodal Functions of Continuous Variables with the
“Simulated Annealing” Algorithm,
{\em ACM Transactions on Mathematical Software} 13 (1987) 262-280.

\item Cord\'{o}n, O., Herrera, F. and Villar, P.:
Analysis and Guidelines to Obtain a Good Uniform Fuzzy Partion
Granularity for Fuzzy Rule-Based System Using Simulated Annealing,
{\em International Journal of Approximate Reasoning} 25 (2000) 187-215.

\item Cot, C. and Catoni, O.:
Piecewise Constant Triangular Cooling Schedules for Generalized Simulated
Annealing Algorithms,
{\em The Annals of Applied Probability} 8 (1998) 375-396.

\item Czy\v{z}ak, P. and Jaszkiewicz, A.:
Pareto Simulated Annealing — A Metahuristic Technique for
Multiple-Objective Combinatorial Optimization,
{\em Journal of Multi-Criteria Decision Analysis} 7 (1998) 34-47.

\item Darema, F., Kirkpatrick, S. and Norton, V.A.:
Parallel Algorithms for Chip Placement by Simulated Annealing,
{\em IBM Journal of Research and Development} 31 (1987) 391-402.

\item Dorea, C.C.Y.:
On the Efficiency of a Continuous Version of the Simulated Annealing Algorothms,
{\em Statistics and Probability Letters} 31 (1997) 247-253.

\item Durand, M.D. and White, S.R.:
Trading Accuracy for Speed in Parallel Simulated Annealing with
Simultaneous Moves,
{\em Parallel Computing} 26 (2000) 135-150.

\item El Gamal, A.A., Hemachandra, L.A., Shperling, I. and Wei, V.K.:
Using Simulated Annealing to Design Good Codes,
{\em IEEE Trans. on Information Theory} 33 (1987) 116-123.

\item Fabian, V.:
Simulated Annealing Simulated,
{\em Computers and Mathematics with Applications} 33 (1997) 81-94.

\item Faigle, U. and Schrader, R.:
On the Convergence of Stationary Distributions in Simulated Annealing
Algorithms,
{\em Information Processing Letter} 27 (1988) 189-194.

\item Francois, O.:
Global Optimization with Exploration/Selection Algorithms and Simulated
Annealing,
{\em The Annals of Applied Probability} 12 (2002) 248-271.

\item Fu, Y. and Anderson, P.W.:
Application of Statistical Mechanics to NP-Complete Problems in
Combinatorial Optimization,
{\em Journal of Physics A}: Math. Gen. 19 (1986) 1605-1620.

\item Gidas, B.:
Nonstationary Markov Chains and Convergence of the Annealing Algorithm,
{\em Journal of Statistical Physics} 39 (1985) 73-131.

\item Gong, G., Liu, Y. and Qian, M.:
An Adaptive Simulated Annealing Algorithm,
{\em Stochastic Processes and Their Applications} 94 (2001) 95-103.

\item Greene, J.W. and Supowit, K.J.:
Simulated Annealing without Rejected Moves,
{\em IEEE Trans. on Computer-Aided Design} 5 (1986) 221-228.

\item Hajek, B.:
Cooling Schedules for Optimal Annealing,
{\em Mathematics of Operations Research} 13 (1988) 311-329.

\item Hamam, Y. and Hindi, K.S.:
Assignment of Program Modules to Processors: A Simulated Annealing Approach,
{\em European Journal of Operational Research} 122 (2000) 509-513.

\item Hapke, M., Jaszkiewicz, A. and Slowinski, R.:
Pareto Simulated Annealing for Fuzzy Multiobjective Combinatorial
Optimization,
{\em Journal of Heuristics} 6 (2000) 329-345.

\item Hastings, W.K.:
Monte Carlo Sampling Methods Using Markov Chains and Their Applications,
{\em Biometrika} 57 (1970) 97-109.

\item Hedar, A.-R. and Fukushima, M.:
Hybrid Simulated Annealing and Direct Search Method for Nonlinear
Unconstrained Global Optimization,
{\em Optimization Methods and Software} 17 (2002) 891-912.

\item Herault, L.:
Rescaled Simulated Annealing — Accelerating Convergence of Simulated
Annaling by Rescaling the States Energies,
{\em Journal of Heuristics} 6 (2000) 215-252.

\item Ingber, L. and Rosen, B.:
Genetic Algorithms and Very Fast Simulated Reannealing: A Comparison,
{\em Math. Comput. Modelling} 16 No. 11 (1992) 87-100.

\item Jacquot, S.:
Simulated Annealing for Stochastic Semilinear Equations on Hilbert Spaces,
{\em Stochastic Processes and Their Applications} 64 (1996) 73-91.

\item Khachaturyan, A.:
Statistical Mechanics Approach in Minimizing a Multivariable Function,
{\em J. Mathematical Physics} 27 (1986) 1834-1838.

\item Kirkpatrick, S.:
Optimization by Simulated Annealing: Quantitative Studies,
{\em Journal of Statistical Physics} 34 (1984) 975-986.

\item Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P.:
Optimization by Simulated Annealing,
{\em Science} 220 (1983) 671-680.

\item Kravitz, S.A. and Rutenbar, R.A.:
Placement by Simulated Annealing on a Multiprocessor,
{\em IEEE Trans. on Computer-Aided Design} 6 (1987) 534-549.

\item Li, Y. and Wang, D.:
A Semi-Infinite Programming Model for Earliness/Tardiness Production
Planning with Simulated Annealing,
{\em Mathematical and Computer Modelling} 26 (1997) 35-42.

\item Liu, J.-L.:
Novel Orthogonal Simulated Annealing with Frcational Factorial Analysis
to Solve Global Optimization Problems,
{\em Engineering Optimization} 37 (2005) 499-523.

\item Locatelli, M.:
Convergence of a Simulated Annealing Algorithm for Continuous Global
Optimization,
{\em Journal of Global Optimization} 18 (2000) 219-234.

\item Locatelli, M.:
Simulated Annealing Algorithms for Continuous Global Optimization:
Convergence Conditions,
{\em Journal of Optimization Theory and Applications} 104 (2000) 121-133.

\item Locatelli, M.:
Convergence and First Hitting Time of Simulated Annealing Algorithms for
Continuous Global Optimization,
{\em Mathematical Methods of Operations Research} 54 (2001) 171-199.

\item L\”{o}we, M.:
Simulated Annealing with Time-Dependent Energy Function via Sobolev
Inequalities,
{\em Stochastic Processes and Their Applications} 63 (1996) 221-223.

\item L\”{o}we, M.:
On the Invariant Measure of Non-Reversible Simulated Annealing,
{\em Statictics and Probability Letters} 36 (1997) 189-193.

\item Lundy, M.:
Applications of the Annealing Algorithm to Combinatorial Problems in
Statistics,
{\em Biometrika} 72 (1985) 191-198.

\item Lundy, M. and Mees, A.:
Convergence of an Annealing Algorithm,
{\em Mathematical Programming} 34 (1986) 111-124.

\item Manuel, D.-A.:
Constructing Efficient Simulated Annealing,
{\em Discrete Applied Mathematics} 77 (1997) 139-159.

\item Mees, A.I. and Tovey, C.:
Constraint Selection and Deterministic Annealing,
{\em Journal of Global Optimization} 27 (2003) 233-247.

\item Meise, C.:
On the Convergence of Parallel Simulated Annealing,
{\em Stochastic Processes and Their Applications} 76 (1998) 99-115.

\item Mitra, D., Romeo, F. and Sangiovanni-Vincentelli, A.:
Convergence and Finite-Time Behavior of Simulated Annealing,
{\em Advances in Applied Probability} 18 (1986) 747-771.

\item Miettinen, K., M\”{a}kela, M.M. and Maaranem, H.:
Efficient Hybrid Methods for Global COntinuous Optimization Based on
Simulated Annealing,
{\em Computers and Operations Research} 33 (2006) 1102-1116.

\item Nourani, Y. and Andresen, B.:
Exploration of NP-Hard Enumeration Problems by Simulated Annealing —
the Spectrum Values of Permanents,
{\em Theoretical Computer Science} 215 (1999) 51-68.

\item Onbasoglu, E. and Ozdamar, L.:
Parallel Simulated Annealing Algorithm in Global Optimization,
{\em Journal of Global Optimization} 19 (2001) 27-50.

\item Orosz, J.E. and Jacobson, S.H.:
Analysis of Static Simulated Annealing Algorithms,
{\em Journal of Optimzation Theory and Applications} 115 (2002) 165-182.

\item Papageorgiou, G., Likas, A. and Stafylopatis, A.:
Improved Exploration in Hopfield Network State-Space through Parameter
Perturbation Driven by Simulated Annealing,
{\em European Journal of Operational Research} 108 (1998) 283-292.

\item Pelletier, M.:
Weak Convergence Rates for Stochastic Approximation with Application
to Multiple Targets and Simulated Annealing,
{\em The Annals of Applied Probability} 8 (1998) 10-44.

\item Rajasenkaran, S.:
On Simulated Annealing and Nested Annealing,
{\em Journal of Global Optimization} 16 (2000) 43-56.

\item Randelman, R.E. and Grest, G.S.:
$N$-City Traveling Salesman Problem: Optimization by Simulated Annealing,
{\em Journal of Statistical Physics} 45 (1986) 885-890.

\item Rees, S. and Ball, R.C.:
Criteria for an Optimum Simulated Annealing Schedule for Problems of the
Travelling Salesman Type,
{\em Journal of Physics A}: Math. Gen. 20 (1987) 1239-1249.

\item Richardt, J., Karl, F. and M\”{u}ller, C.:
Connections between Fuzzy Theory, Simulated Annealing, and Convex Duality,
{\em Fuzzy Sets and Systems} 96 (1998) 307-334.

\item Romeijn, H.E., Zabinsky, Z.B., Graesser, D.L. and Neogi, S.:
New Reflection Generator for Simulated Annealing in Mixed-Integer/Continuous
Global Optimization,
{\em Journal of Optimization Theory and Applications} 101 (1999) 403-427.

\item Siarry, P., Berthiau, G., Durbin, F. and Haussy, J.:
Enhanced Simulated Annealing for Globally Minimizing Functions of Many-Continuous
Variables,
{\em ACM Transactions on Mathematical Software} 23 (1997) 209-228.

\item Szu, H.H. and Hartley, R.L.:
Nonconvex Optimization by Fast Simulated Annealing,
{\em Proceedings of the IEEE} 75 (1987) 1538-1540.

\item Szu, H. and Hartley, R.:
Fast Simulated Annealing,
{\em Physics Letters A} 122 (1987) 157-162.

\item Triki, E., Collette, Y. and Siarry, P.:
A Theoretical Study on the Behavior of Simulated Annealing Leading to
a New Cooling Schedule,
{\em European Journal of Operational Research} 166 (2005) 77-92.

\item Trouve, A.:
Cycle Decompositions and Simulated Annealing,
{\em SIAM J. Control and Optimization} 34 (1996) 966-986.

\item Tsitsiklis, J.N.:
Markov Chains with Rare Transitions and Simulated Annealing,
{\em Mathematics of Operations Research} 14 (1989) 70-90.

\item Van Ginneken, L.P.P.P. and Otten, R.H.J.M.:
An Inner Loop Criterion for Simulated Annealing,
{\em Physics Letters A} 130 (1988) 429-435.

\item Vanderbilt, D. and Louie, S.G.:
A Monte Carlo Simulated Annealing Approach to Optimization Over Continuous
Variables,
{\em Journal of Computational Physics} 56 (1984) 259-271.

\item Vecchi, M.P. and Kirkpatrick, S.:
Global Wiring by Simulated Annealing,
{\em IEEE Trans. on Computer-Aided Design} 2 (1983) 215-222.

\item Wang, P.P. and Chen, D.-S.:
Continuous Optimization by a Variant of Simulated Annealing,
{\em Computational Optimization and Applications} 6 (1996) 59-71.

\item Yang, R.L.:
Convergence of the Simulated Annealing Algorithm for Continuous Global
Optimization,
{\em Journal of Optimization Theory and Applications} 104 (2000) 691-716.

\begin{equation}{\label{q}}\tag{Q}\mbox{}\end{equation}

Swarm Intelligence.

\item Abdelbar, A.M. and Abdelshahid, S.:
Swarm optimization with instinct-driven particles,
The Congress on Evolutionary Computation, 2003, pp.777-782.

\item Abdelbar, A.M. and Abdelshahid, S.:
Instinct-based PSO with local search applied to satisfiability,
Proceedings of the IEEE International Joint Conference on Neural Networks, 2004, pp.2291-2295.

\item Al-Kazemi, B. and Mohan, C.K.:
Training Feedforward Neural Networks Using Multi-Phase Particle Swarm Optimization,
{\em Proceedings of the $9$th International Conference on Neural Information Processing, 2002, pp.2615-2619.

\item Allahverdi, A. and Al-Anzi, F.S.:
A PSO and a Tabu Search Heuristics for the Assembly Scheduling Problem of the Two-Stage Distributed Database Application,
{\em Computers and Operations Research} 33 (2006) 1056-1080.

\item Bartz-Beielstein, T., Limbourg, P., Mehnen, J., Schmitt, K., Parsopoulos, K.E. and Vrahatis, M.N.:
Particle swarm optimizers for Pareto optimization with enhanced archiving techniques,
The Congress on Evolutionary Computation, 2003, pp.1780-1787.

\item Brits, R., Engelbrecht, A.P. and Van den Bergh, F.:
Solving systems of unconstrained equations using particle swarm optimization,
Proceedings of the IEEE International Conference on Systems, Man and
Cybernetics, 2002, pp. 100-105.

\item Chatterjee, A. and Siarry, P.:
Nonlinear Inertia Weight Variation for Dynamic Adaptation in Particle
Swarm Optimization,
{\em Computers and Operations Research} 33 (2006) 859-871.

\item Clerc, M.:
The Swarm and the Queen: Towards a Deterministic and Adaptive Paricle Swarm
Optimization,
IEEE, 1999, pp.1951- 1957.

\item Clerc, M. and Kennedy, J.:
The Particle Swarm — Explosion, Stability, and Convergence in a
Multidimensional Complex Space,
{\em IEEE Trans. on Evolutionary Computation}6 (2002) 58-73.

\item Coath, G. and Halgamuge, S.K.:
A comparison of constraint-handling methods for the application of particle
swarm optimization to constrained nonlinear optimization problems,
The Congress on Evolutionary Computation, 2003, pp.2419-2425.

\item Coello, C.A.C., Pulido, G.T. and Lechuga, M.S.:
Handling Multiple Objectives with Particle Swarm Optimization,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 256-279.

\item Cui, Z., Zeng, J. and Cai X.:
A new stochastic particle swarm optimizer,
The Congress on Evolutionary Computation, 2004, pp.316-319.

\item Dong, Y., Tang, J., Xu, B. and Wang, D.:
An Application of Swarm Optimization to Nonlinear Programming,
{\em Computers and Mathematics with Applications} 49 (2005) 1655-1668.

\item Eberhart, R.C. and Shi, Y.:
Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization,
IEEE, 2000, pp.84-88.

\item Eberhart, R.C. and Shi, Y.:
Particle swarm optimization: Developments, applications and resources,
Proceedings of the IEEE Conference on Evolutionary Computation, 2001, pp.81-86.

\item Elgebede, C.:
Structural Reliability Assessment Based on Particles Swarm Optimization,
{\em Structural Safety} 27 (2005) 171-186.

\item Engelbrecht, A.P., Masiye, B.S. and Pampara, G.:
Niching ability of basic particle swarm optimization algorithms.
IEEE Proceedings, Swarm Intelligence Symposium, 2005, pp.397-400.

\item Fan, H.:
A Modification to Particle Swarm Optimization Algorithm,
{\em Engineering Computations} 19 (2002) 970-989.

\item Fan, S.-K. and Zahara, E.:
A Hybrid Simplex Search and Particle Swarm Optimization for Unconstrained Optimization,
{\em European Journal of Operational Research} 181 (2007) 527-548.

\item Fan, S.-K., Liang, Y.-C. and Zahara, E.:
Hybrid Simplex Search and Particle Swarm Optimization for the Global Optimization of Multimodal Functions,
{\em Engineering Optimization} 36 (2004) 401-418.

\item Fourie, P.C. and Groenwold, A.A.:
The Particle Swarm Optimization Algorithm in Size and Shape Optimization,
{\em structural and Multidisciplinary Optimization} 23 (2002) 259-267.

\item Franken, N. and Engelbrecht, P.:
Particle Swarm Optimization Approaches to Coevolve Strategies for the Iterated Prisoner’s Dilemma,
{\em IEEE Trans. on Evolutionary Computation} 9 (2005) 562-579.

\item Higashi, N. and Iba, H.:
Particle Swarm Optimization with Gaussian Mutation,
{\em IEEE} 2003 ?? 72-79.

\item Ho, L.S., Yang, S., Ni, G., Lo, E.W. and Wong, H.C.,
A Particle Swarm Optimization-Based Method for Multiobjective Design Optimization,
{\em IEEE Trans. on Magnetics} 41 (2005) 1756-1759.

\item Jerald, J., Asokan, P., Prabaharan, G. and Saravanan, R.:
Scheduling Optimization of Flexible Manufacturing Systems Using Particle Swarm Optimization Algorithm,
{\em International Journal of Advanced Manufacturing Technology} 25 (2005) 964-971.

\item Jiang, C. and Bompard, E.:
A Hybrid Method of Chaotic Particle Swarm Optimization and Linear
Interior for Reactive Power Optimization,
{\em Mathematics and Computers in Simulation} 68 (2005) 57-65.

\item Juang, C.-F., Chung, I.-F. and Hsu, C.-H.:
Automatic Construction of Feedforward/REcurrent Fuzzy Systems
by Clustering-Aided Simplex Particle Swarm Optimization,
{\em Fuzzy Sets and Systems} 158 (2007) 1979-1996.

\item Kaewkamnerdpong, B. and Bentley, P.J.: (Swarm Intelligence)
Perceptive particle swarm optimisation: an investigation,
IEEE Proceedings, Swarm Intelligence Symposium, 2005, pp.169-176.

\item Kennedy, J.:
The particle swarm: social adaptation of knowledge,
IEEE International Conference on Evolutionary Computation, 1997,
pp.303-308.

\item Kennedy, J.:
Why does it need velocity?
IEEE Proceedings, Swarm Intelligence Symposium, 2005, pp.38-44.

\item Kennedy, J. and Eberhart, R.:
Particle swarm optimization,
IEEE International Conference on Neural Networks, 1995, pp.1942-1948.

\item Kennedy, J. and Mendes, R.:
Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms,
Proceedings of the IEEE International Workshop on Soft Computing in Industrial Applications, 2003, pp.45-50.

\item Kou, X., Liu, S., Zhang, J. and Zheng, W.:
Co-Evolutionary Particle Swarm Optimization to Solve Constrained Optimization Problems,
{\em Computers and Mathematics with Applications} 57 (2009) 1776-1784.

\item Krohling, R.A.:
Gaussian Swarm: A Novel Particle Swarm Optimization Algorithm,
{\em Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems}, 2004, 372-376.

\item Kuo, R.J. and Huang, C.C.:
Application of Particle Swarm Optimization Algorithm for Solving Bi-Level Linear Programming Problem,
{\em Computers and Mathematics with Applications} 58 (2009) 678-685.

\item Li, N., Liu, F., Sun, D. and Huang, C.:
Particle Swarm Optimization for Constrained Layout Optimization,
{\em Proceedings of the 5th IEEE World Congress on Intelligent Control and Automation}, 2004, pp.15-19.

\item Liew, K.M., Tan, P.K. and Ray, T.:
Leader Identification and Leader Selection: Its Effect on a Swarm’s Performance for Multiobjective Design Optimization Problems,
{\em structural and Multidisciplinary Optimization} 28 (2004) 156-169.

\item Li, A., Wang, L., Li, J. and Ji, C.: (Swarm Intelligence)
Application of Immune Algorithm-Based Particle Swarm Optimization for Optimized Load Distribution Among Cascade Hydropower Stations,
{\em Computers and Mathematics with Applications} 57 (2009) 1785-1791.

\item Li, N., Qin, Y.-Q. and Sun, D.-B. and Zou, T.:
Particle Swarm Optimization with Mutation Operator,
{\em Proceedings of the IEEE Third International Conference on Machine Learning and Cybernetics, 2004, pp.2251-2256.

\item Lian, Z., Gu, X. and Jiao, B.:
A Similar Particle Swarm Optimization Algorithm for Permutation Flowshop
Scheduling to Minimize Makespan,
{\em Applied Mathematics and Computation} 175 (2006) 773-785.

\item Liu, B., Wang, L., Jin, Y.-H., Tang, F. and Huang, D.-X.:
Improved Particle Swarm Optimization Combined with Chaos,
{\em Chaos, Solitions and Fractals} 25 (2005) 1261-1271.

\item Mendes, R., Kennedy, J. and Neves, J.:
The Fully Informed Particle Swarm: Simpler, Maybe Better,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 204-210.

\item Messerschmidt, L. and Engelbrecht, A.P.:
Learning to Play Games Using a PSO-Based Competitive Learning Approach,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 280-288.

\item Pan, H., Wang, L. and Liu, B.:
Particle Swarm Optimization for Function Optimization in Noisy Environment,
{\em Applied Mathematics and Computation} 181 (2006) 908-919.

\item Pang, W., Wang, K.-P., Zhou, C.-G. and Dong, L.-J.:
Fuzzy Discrete Particle Swarm Optimization for Solving Traveling Salesman
Problem,
{\em IEEE Proceedings of the Fourth International Conference on Computer
and Information Technology, 2004, pp.??

\item Paquet, U. and Engelbrecht, A.P.:
Training Support Vector Machines with Particle Swarms,
International Joint Conference on Neural Networks, Portland, OR, 2003

\item Parsopoulos, K.E. and Vrahatis, M.N.:
Particle swarm optimization method in multiobjective problems,
Proceedings of the ACM Symposium on Applied Computing, 2002, pp.603-607.

\item Parsopoulos, K.E. and Vrahatis, M.N.:
Recent Approaches to Global Optimization Problems through Particle
Swarm Optimization,
{\em Natural Computing} 1 (2002) 235-306.

\item Parsopoulos, K.E. and Vrahatis, M.N.:
Investigating the existence of function roots using particle swarm optimization
The Congress on Evolutionary Computation, 2003, pp.1448-1455.

\item Parsopoulos, K.E. and Vrahatis, M.N.:
On the Computation of all Global Minimizers through Particle Swarm
Optimization,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 211-224.

\item Parsopoulos, K.E. and Vrahatis, M.N.:
Unified particle swarm optimization for tackling operations research problems
IEEE Proceedings, Swarm Intelligence Symposium, 2005, pp.53-59.

\item Paterlini, S. and Krink, T.:
Differential Evolution and Particle Swarm Optimization in Partitonal Clustering,
{\em Computational Statistics and Data Analysis} 50 (2006) 1220-1247.

\item Peer, E.S., van den Bergh, F. and Engelbrecht, A.P.:
Using neighbourhoods with the guaranteed convergence PSO,
{\em Swarm Intelligence Symposium, Proceedings of the 2003 IEEE,
pp.235-242.

\item Ratnaweera, A., Halgamuge, S.K. and Watson, H.C.:
Self-Organizing Hierarchical Particle Swarm Optimizer with Time-Varying
Acceleration Coefficients,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 240-255.

\item Salman, A., Ahmad, I. and Al-Madani, S.:
Particle Swarm Optimization for Task Assignment Problem,
{\em Microprocessors and Microsystems} 26 (2002) 363-371.

\item Secrest, B.R. and Lamont, G.B.:
Visualizing particle swarm optimization – Gaussian particle swarm
optimization
IEEE Proceedings, Swarm Intelligence Symposium, 2003, pp.198-204.

\item Schutte, J.F. and Groenwold, A.A.:
A Study of Global Optimization Using Particle Swarms,
{\em Journal of Global Optimization} 31 (2005) 93-108.

\item Schutte, J.F., Reinbolt, J.A., Fregly, B.J., Haftka, R.T. and George, A.D.:
Parallel Global Optimization with the Particle Swarm Algorothm,
{\em International Journal for Numerical Methods in Engineering} 61 (2004) 2296-2315.

\item Shelokar, P.S., Jayaraman, V.K. and Kulkarni, B.D.:
Ant Algorithm for Single and Multiobjective Reliability Optimization Problems,
{\em Quality and Reliability Engineering International} 18 (2002) 497-514.

\item Shelokar, P.S., Siarry, P., Jayaraman, V.K. and Kulkarni, B.D.:
Particle Swarm and Ant Colony Algorithms Hybridzed for Improved
Continuous Optimization,
{\em Applied Mathematics and Computation} 188 (2007) 129-142.

\item Shi, Y. and Eberhart, R.:
Modified particle swarm optimizer,
Proceedings of the IEEE Conference on Evolutionary Computation, 1998,
pp.69-73.

\item Shi, Y. and Eberhart, R.C.:
Fuzzy adaptive particle swarm optimization
Proceedings of the IEEE Congress on Evolutionary Computation, 2001,
pp.101-106.

\item Stacey, A., Jancic, M. and Grundy, I.:
Particle swarm optimization with mutation,
The Congress on Evolutionary Computation, 2003, pp.1425-1430.

\item Tasgetiren, M.F., Liang, Y.-C., Sevkli, M. and Gencyilmaz, G.:
A Particle Swarm Optimization Algorithm for Makespan and Total Folowtime
Minimization in the Permutation Flowshop Sequencing Problem,
{\em European Journal of Operational Research} 177 (2007) 1930-1947.

\item Tsai, C.-Y. and Yeh, S.-W.:
A Multiple Objective Particle Swarm Optimization Approach for
Inventory Classification,
{\em International Journal of Production Economics} 114 (2008) 656-666.

\item Van den Bergh, F. and Engelbrecht, A.P.:
A new locally convergent particle swarm optimiser,
Proceedings of the IEEE International Conference on Systems, Man and
Cybernetics, 2002, pp.94-99.

\item van den Bergh, F. and Engelbrecht, A.P.:
A Cooperative Approach to Particle Swarm Optimization,
{\em IEEE Transactions on Evolutionary Computation} 8 (2004) 225-239.

\item Villalobos-Arias, M.A., Pulido, G.T. and Coello C.C.A.:
A proposal to use stripes to maintain diversity in a multi-objective particle swarm optimizer
IEEE Proceedings, Swarm Intelligence Symposium, 2005, pp.22-29.

\item Wang, K.-P., Huang, L., Zhou, C.-G. and Pang, W.:
Particle Swarm Optimization for Traveling Salesman Problem,
{\em Proceedings of the Second International Conference on Machine Learning
and Cybernetics}, 2003, 1583-1585.

\item Xu, J.-J. and Xin, Z.-H.:
An Extended Particle Swarm Optimizer,
Proceedings of the 19th IEEE International Parallel and Distributed
Processing Symposium, 2005, pp.193a-193a.

\item Yasuda, K., Ide, A. and Iwasaki, N.:
Adaptive particle swarm optimization
Proceedings of the IEEE International Conference on Systems, Man and
Cybernetics, 2003, pp.1554-1559.

\item Yin, P.-Y. and Wang, J.-Y.:
A Particle Swarm Optimizzation to the Nonlinear Resource Allocation Problem,
{\em Applied Mathematics and Computation} 183 (2006) 232-242.

\item Zhang, Q.-L., Li, X. and Tran, Q.-A.:
Particle Swarm Optimization Based Hybrid Intelligent Algorithm,
{\em Proceedings of the Second International Conference on Maching Learning
and Cybernetics}, 2003, pp.1648-1650.

\item Zhang, J.-R., Zhang, J., Lok, T.-M. and Lyu, M.R.:
A Hybrid Particle Swarm Optimization — Back-Propogation Algorithm
for Feedforward Neural Network Training,
{\em Applied Mathematics and Computation} 185 (2007) 1026-1037.

\item Zhang, L.-P., Yu, H.-J. and Hu, S.-X.:
Optimal Choice of Parameters for Particle Swarm Optimization,
{\em Journal of Zhejiang Science} 6A (2005) 528-534.

\item Zhao, Y., Zu, W. and Zeng, H.: (Swarm Intelligence)
A Modified Particle Swarm Optimization via Particle Visual Modeling Analysis,
{\em Computers and Mathematics with Applications} 57 (2009) 2022-2029.

\item Zheng, X. and Liu, H.:
A Hybrid Vertical Mutation and Self-Adaptation Based MOPSO,
{\em Computers and Mathematics with Applications} 57 (2009) 2030-2038.

\begin{equation}{\label{r}}\tag{R}\mbox{}\end{equation}

Tabu Search.

\item Ba\v{g}is, A.:
Determining Fuzzy Membership Functions with Tabu Search — An Application
to Control,
{\em Fuzzy Sets and Systems} 139 (2003) 209-225.

\item Burke, E.K., Kendall, G. and Soubeiga, E.:
A Tabu Search Hyperheuristics for Timetabling and Rostering,
{\em Journal of Heuristics} 9 (2003) 451-470.

\item Chelouah, R. and Siarry, P.:
Tabu Search Applied to Global Optimization,
{\em European Journal of Operational Research} 123 (2000) 256-270.

\item Dell’Amico, M. and Trubian, M.:
Applying Tabu Search to the Job-Shop Scheduling Problem,
{\em Annals of Operations Research} 41 (1993) 231-252.

\item Faigle, U. and Kern, W.:
Some Convergence Results for Probabilistic Tabu Search,
{\em ORSA Journal on Computing} 4 (1992) 32-37.

\item Garcia, C.G., P\'{e}rez-Brito, D., Campos, V. and Mart\'{i}, R.:
Variable Neighborhood Search for the Linear Ordering Problem,
{\em Computers and Operations Research} 33 (2006) 3549-3565.

\item Glover, F.:
Tabu Search — Part I,
{\em ORSA Journal on Computing} 1 (1989) 190-206.

\item Glover, F.:
Tabu Search — Part II,
{\em ORSA Journal on Computing} 2 (1990) 4-32.

\item Glover, F.:
Tabu Search for Nonlinear and Parametric Optimization,
{\em Discrete Applied Mathematics} 49 (1994) 231-255.

\item Glover, F.: (Tabu Search)
Parametric Tabu-Search for Mixed Integer Programs,
{\em Computers and Operations Research} 33 (2006) 2449-2494.

\item Glover, F. and Hanafi, S.:
Tabu Search and Finite Convergence,
{\em Discrete Applied Mahematics} 119 (2002) 3-36.

\item Glover, F., Kelley, J.P. and Laguna, M.:
Genetic Algorithms and Tabu Search: Hybrids for Optimization,
{\em Computers and Operations Research} 22 (1995) 111-134.

\item Gupta, J.N.D., Palanimuthu, N. and Chen, C.-L.:
Designing a Tabu Search Algorithm for the Two-Stage Flow Shop Problem
with Secondary Criterion,
{\em Production Planning and Control} 10 (1999) 251-265.

\item Hanafi, S.:
On the Convergence of Tabu Search,
{\em Journal of Heuristics} 7 (2000) 47-58.

\item Hedar, A.-R. and Fukushima, M.:
Tabu Search Directed by Direct Search Methods for Nonlinear Global
Optimization,
{\em European Journal of Operational Research} 170 (2006) 329-349.

\item J\'{o}zefowska, J., Walig\'{o}ra, G. and Weglarz, J.:
Tabu List Management Methods for a Discrete-Continuous Scheduling Problem,
{\em European Journal of Operational Research} 137 (2002) 288-302.

\item Kulture-Konak, S,, Smith, A.E. and Norman, B.A.:
Multi-Objective Tabu Search Using Multinomial Probability Mass Function,
{\em European Journal of Operational Research} 169 (2006) 918-931.

\item Laguna, M. and Glover, F.:
Integrating Target Analysis and Tabu Search for Improved Scheduling Systems,
{\em Expert Systems with Applications} 6 (1993) 287-297.

\item Lokketangen, A. and Glover, F.:
Solving Zero-One Mixed Integer Programming Problems Using Tabu Search,
{\em European Journal of Operational Research} 106 (1998) 624-658.

\item Moilanen, A.:
Parameterization of a Metapopulation Model: An Empirical Comparison of
Several Different Genetic Algorithms, Simulated Annealing and Tabu Search,
{\em IEEE International Conference on Evolutionary Computation}, 1995.

\item Mooney, E.L. and Rardin, R.L.: (Tabu Search)(Tabu Search and Simulated Annealing in Scheduling)
Tabu Search for a Class of Scheduling Problems,
{\em Annals of Operations Research} 41 (1993) 253-278.

\item Nowicki, E. and Smutnicki,, C.: (Tabu Search)(Tabu Search and Simulated Annealing in Scheduling)
A Fast Taboo Search Algorithm for the Job Shop Problem,
{\em Management Science} 42 (1996) 797-813.

\item Nowicki, E. and Smutnicki,, C.: (Tabu Search)(Tabu Search and Simulated Annealing in Scheduling)
A Fast Tabu Search Algorithm for the Permutation Flow-Shop Problem,
{\em European Journal of Operational Research} 91 (1996) 160-175.

\item Pirlot, M.:
General Local Search Methods,
{\em European Journal of Operational Research} 92 (1996) 493-511.

\item Sexton, R.S., Alidaee, B., Dorsey, R.E. and Johnson, J.D.:
Global Optimization for Artificial Neural Networks: A Tabu Search Application,
{\em European Journal of Operational Research} 106 (1998) 570-584.

\item Siarry, P. and Berthiau, G.:
Fitting of Tabu Search to Optimize Functions of Continuous Variables,
{\em International Journal for Numerical Methods in Engineering} 40 (1997)
2449-2457.

\item Wan, G., Yen, B. P.-C.:
Tabu Search for Single Machine Scheduling with Distinct Due Windows and
Weighted Earliness/Tardiness Penalties,
{\em European Journal of Operational Research} 142 (2002) 271-281.

\item Wang, L. and Zheng, D.-Z.: (Tabu Search)(Tabu Search and Simulated Annealing in Scheduling)
An Effective Hybrid Optimization Strategy for Job-Shop Scheduling Problems,
{\em Computers and Operations Research} 28 (2001) 585-596.

\begin{equation}{\label{t}}\tag{T}\mbox{}\end{equation}

Fuzzy Dynamical Systems.

\item Bassanezi, R.C., de Barros, L.C. and Tonelli, P.A.:
Attractors and Asymptotic Stability for Fuzzy Dynamical Systems,
{\em Fuzzy Sets and Systems} 113 (2000) 473-483.

\item Bhattacharyya, M.:
Fuzzy Markovian Decision Processes,
{\em Fuzzy Sets and Systems} 99 (1998) 273-282.

\item Cao, S.G. and Rees, N.W.:
Identification of Dynamic Fuzzy Models,
{\em Fuzzy Sets and Systems} 74 (1995) 307-320.

\item Cao, S.-G., Rees, N.W. and Fang, G.:
Analysis and Design of Fuzzy Control Systems Using Dynamic Fuzzy-State
Space Models,
{\em IEEE Trans. on Fuzzy Systems} 7 (1999) 192-199.

\item Ding, Z, Ma, M. and Kandel, A.:
On the Observability of Fuzzy Dynamical Control Systems (I),
{\em Fuzzy Sets and Systems} 111 (2000) 225-236.

\item Dumitrescu, D.:
Entropy of Fuzzy Dynamical Systems,
{\em Fuzzy Sets and Systems} 70 (1995) 45-57.

\item Dumitrescu, D., H\v{a}loiu, C. and Dumitrescu, A.:
Generators of Fuzzy Dynamical Systems,
{\em Fuzzy Sets and Systems} 113 (2000) 447-452.

\item Edwards, D., Choi, H.T.:
Use of Fuzzy Logic to Calculate the Statistical Properties of Strange
Attractors in Chaotic Systems,
{\em Fuzzy Sets and Systems} 88 (1997) 205-217.

\item Feng, Y.:
Fuzzy Stochastic Differential Systems,
{\em Fuzzy Sets and Systems} 115 (2000) 351-363.

\item Feng, Y.:
The Solutions of Linear Fuzzy Stochastic Differential Systems,
{\em Fuzzy Sets and Systems} 140 (2003) 541-554.

\item Giles, C.L., Omlin, C.W. and Thornber, K.K.:
Equivalence in Knowledge Representation: Automata, Recurrent Neural
Networks, and Dynamical Fuzzy Systems,
{\em Proceedings of the IEEE}.

\item Johansen, T.A., Shorten, R. and Murray-Smith, R.:
On the Interpretation and Identification of Dynamic Takagi-Sugeno Fuzzy
Models,
{\em IEEE Trans. on Fuzzy Systems} 8 (2000) 297-313.

\item Kurano, M., Yasuda, M., Nakagami, J.-I. and Yoshida, Y. :
A Limit Theorem in Some Dynamic Fuzzy Systems,
{\em Fuzzy Sets and Systems} 51 (1992) 83-88.

\item Kurano, M., Yasuda, M., Nakagami, J.-I. and Yoshida, Y.:
Markov-Type Fuzzy Decision Processes with a Discounted Reward on a Closed
Interval,
{\em European Journal of Operational Research} 92 (1996) 649-662,

\item Liu, P.:
Fuzzy-Valued Markov Processes and Their Properties,
{\em Fuzzy Sets and Systems} 91 (1997) 45-52.

\item Kloeden, P.E.:
Fuzzy Dynamical Systems,
{\em Fuzzy Sets and Systems} 7 (1982) 275-296.

\item Markechov\'{a}, D.:
A Note to the Kolmogorov-Sinaj Entropy of Fuzzy Dynamical Systems,
{\em Fuzzy Sets and Systems} 64 (1994) 87-90.

\item Park, J.Y., Jung, I.H. and Lee, M.J.:
Almost Periodic Solutions of Fuzzy Systems,
{\em Fuzzy Sets and Systems} 119 (2001) 367-373.

\item Srivastava, P., Khare, M. and Srivastara, Y.K.:
Fuzzy Dynamical Systems-Inverse and Direct Spectra,
{\em Fuzzy Sets and Systems} 113 (2000) 439-445.

\item Yoshida, Y.:
A Stopping Game in a Stochastic and Fuzzy Environment,
{\em Mathematical and Computer Modeling} 30 (1999) 147-158.

\item Yoshida, Y.:
A Time-Average Fuzzy Reward Criterion in Fuzzy Decision Processes,
{\em Information Sciences} 110 (1998) 103-112.

\item Yoshida, Y.:
A Minimax Theorem for Zero-Sume Stopping Games in Dynamic Fuzzy Systems,
{\em Mathematical and Computer Modeling} 29 (1999) 19-33.

\item Yoshida, Y.:
A Limit Theorem in Dynamic Fuzzy Systems with Transitive Fuzzy Relations,
{\em Fuzzy Sets and Systems} 109 (2000) 371-378.

\item Yoshida, Y.:
A Continuous-Time Dynamic Fuzzy System (I): A Limit Theorem,
{\em Fuzzy Sets and Systems} 113 (2000) 453- 460.

\item Yoshida, Y.:
A Continuous-Time Dynamic Fuzzy System (II): Fuzzy Potentials,
{\em Fuzzy Sets and Systems} 113 (2000) 461-472.

\item Yoshida, Y.:
A Zero-Sum Stopping Game in a Continuous-Time Dynamic Fuzzy System,
{\em Mathematical and Computer Modeling} 34 (2001) 603-614.

\item Yoshida, Y.:
Fuzzy Stopping in Continuous-Time Dynamic Fuzzy Systems,
{\em Fuzzy Sets and Systems} 132 (2002) 291-301.

\item Yoshida, Y.:
Continuous-Time Fuzzy Decision Processes with Discounted Rewards,
{\em Fuzzy Sets and Systems} 139 (2003) 333-348.

\item Yoshida, Y, Yasuda, M., Nakagami, J. and Kurano, M.:
Optimal Stopping Problems in a Stochastic and Fuzzy System,
{\em Journal of Mathematical Analysis and Applications} 246 (2000) 135-149.

\item Yoshida, Y, Yasuda, M., Nakagami, J. and Kurano, M.:
Fuzzy Stopping Problems in Continuous-Time Fuzzy Stochastic Systems,
{\em Fuzzy Sets and Systems} 139 (2003) 349-362.

\begin{equation}{\label{s}}\tag{S}\mbox{}\end{equation}

Hybrid Methods.

\item Adler, D.:
Genetic Algorithms and Simulated Annealing: A Marriage Proposal,
{\em IEEE International Conference on Neural Networks}, 1993, 1104-1109.

\item Alves, M.J. and Cl\'{i}maco, J.:
An Interactive Method for 0-1 Multiobjective Problems Using Simulated
Annealing and Tabu Search,
{\em Journal of Heuristics} 6 (2000) 385-403.

\item Barton, R.R. and Ivey, J.S.: (Random Search)
Nelder-Mead Simplex Modifications for Simulation Optimization,
{\em Management Science} 42 (1996) 954-973.

\item Birbil, S.I. and Fang, S.-C.:
An Electromagnetism-like Mechanism for Global Optiomization,
{\em Journal of Global Optimization} 25 (2003) 263-282.

\item Birbil, S.I., Fang, S.-C. and Sheu, R.-L.:
On the Convergence of a Population-Based Global Optimization Algorithm,
{\em Journal of Global Optimization} 30 (2004) 301-318.

\item Bozejko, W. and Wodecki, M.:
On the Theoretical Properties of Swap Multimoves,
{\em Operations Research Letters} 35 (2007) 227-231.

\item Chelouah, R. and Siarry, P.:
Genetic and Nelder-Mead Algorithms Hybridized for a More Accurate Global
Optimization of Continuous Multiminima Functions,
{\em European Journal of Operational Research} 148 (2003) 335-348.

\item Chelouah, R. and Siarry, P.:
A Hybrid Method Combining Continuous Tabu Search and Nelder-Mead Simplex
Algorithms for the Global Optimization of Multiminima Functions,
{\em European Journal of Operational Research} 161 (2005) 636-654.

\item Coello, C.A.C. and Cort\'{e}s, N.C.:
Hybridizing Genetic Algorithm with an Artificial Immune System for
Global Optimization,
{\em Enginering Optimization} 36 (2004) 607-634.

\item Fan, S.-K., Liang, Y.-C. and Zahara, E.:
Hybrid Simplex Search and Particle Swarm Optimization for the Global
Optimization of Multimodal Functions,
{\em Engineering Optimization} 36 (2004) 401-418.

\item Fan, S.-K. and Zahara, E.:
A Hybrid Simplex Search and Particle Swarm Optimization for Unconstrained
Optimization,
{\em European Journal of Operational Research} 181 (2007) 527-548.

\item Garc\'{i}a-Lopez, F., Meli\'{a}n-Batista, B. and Moreno-P\{e}rez, J.A.:
The Parallel Variable Neighborhood Search for the $p$-Median Problem,
{\em Journal of Heuristics} 8 (2002) 375-388.

\item Hansen, P., Miladenovi\'{c}, N. and Perez-Brito, D.:
Variable Neighborhood Decomposition Search,
{\em Journal of Heuristics} 7 (2001) 335-350.

\item Jacobson, S.H. and Y\”{u}cesan, E.:
Analyzing the Performance of Generalized Hill Climbing Algorithms,
{\em Journal of Heuristics} 10 (2004) 387-405.

\item Kannan, S., Slochanal, M.R. and Padhy, N.P.:
Applications and Comparison of Metaheuristic Techniques to Generation
Expansion Planning Problem,
{\em IEEE Trans. on Power Systems} 20 (2005) 466-475.

\item Nazareth, L. and Tseng, P.:
Gilding the Lily: A Variant of the Nelder-Mead Algorithm Based on
Golden-Section Search,
{\em Computational Optimization and Applications} 22 (2002) 133-144.

\item Olsson, D.M. and Nelson, L.S.:
The Nelder-Mead Simplex Procedure for Function Minimization,
{\em Techonometrics} 17 (1975) 45-51.

\item Ovacik, I.M., Rajagopalan, S. and Uzsoy, R.:
Integrating Interval Estimates of Global Optima and Local Search Methods
for Combinatorial Optimization Problems,
{\em Journal of Heuristics} 6 (2000) 481-500.

\item Paterlini, S. and Krink, T.:
Differential Evolution and Particle Swarm Optimization in Partitonal Clustering,
{\em Computational Statistics and Data Analysis} 50 (2006) 1220-1247.

\item Shapiro, A.F.:
The Merging of Neural Networks, Fuzzy Logic and Genetic Algorithms,
{\em Insurance: Mathematics and Economics} 31 (2002) 115-131.

\item Takahama, T. and Sakai, S.:
Constrained Optimization by Applying $\alpha$-Constrained Method to the
Nonlinear Simplex Method with Mutations,
{\em IEEE Trans. on Evolutionary Computation} 9 (2005) 437- 451.

\item Trafalis, T.B. and Kasap, S.:
A Novel Metaheuristics Approach for Continuous Global Optimization,
{\em Journal of Global Optimization} 23 (2002) 171-190.

\item Vigo, D. and Maniezzo, V.:
A Genetic/Tabu Thresholding Hybrid Algorithm for the Process Allocation
Problem,
{\em Journal of Heuristics} 3 (1997) 91-110.

\item Wang, X.-H. and Li, J.-J.:
Hybrid Particle Swarm Optimization with Simulated Annealing,
{\em Proceedings of the Third International Conference on Machine Learning and Cybernetics}, 2004, pp.2402-2405.

\item Wang, Y.-J., Zhang, J.-S. and Zhang, Y.-F.:
A Fast Hybrid Algorithm for Global Optimization,
{\em Proceedings of the Fourth International Conference on Learning and Cybernetics}, 2005, pp.18-21.

\item Wright, M.:
Subcost-Guided Search — Experiments with Timetabling Problems,
{\em Journal of Heuristics} 7 (2001) 251-260.

\item Yen, J., Liao, J.C., Lee, B. and Randolph, D.:
A Hybrid Approach to Modeling Metabolic Systems Using Genetic Algorithm and Simplex Method,
{\em IEEE Trans. on Systems, Man, and Cybernetics} — Part B 28 (1998) 173-191.

\item Yiu, K.F.C., Liu, Y. and Teo, K.L.:
A Hybrid Descent Method for Global Optimization,
{\em Journal of Global Optimization} 28 (2004) 229-238.

\item Yoo, J. and Hajela, P.:
Fuzzy Multicriterion Design Using Immune Network Simulation,
{\em structural and Multidisciplinary Optimization} 22 (2001) 188-197.

\item Yun, Y. and Gen, M.:
Performance Analysis of Adaptive Genetic Algorithms with Fuzzy Logic and Heuristics,
{\em Fuzzy Optimization and Decision Making} 2 (2003) 161-175.

\item Zhang, W.-J. and Xie, X.-F.:
DEPSO: hybrid particle swarm with differential evolution operator,
IEEE International Conference on Systems, Man and Cybernetics, 2003,
pp.3816-3821.