Genetic search algorithms to fuzzy multiobjective games: A mathematica implementation

International Conference on Applied Computer Science - Proceedings

Volumn , Issue , 2010, Pages 351-359

  Keller, Andre A ^a  

^a UNIV LILLE   (France)

Author keywords

Fuzzy matrix games; Genetic algorithm; Mathematica; Multiple objectives; Nelder Meade algorithm

Indexed keywords

BIMATRIX GAMES; DECISION MAKERS; EXHAUSTIVE SEARCH; FUZZY ENVIRONMENTS; FUZZY MATRIX; GENETIC SEARCH ALGORITHMS; GENOCOP III; HIGH-PERFORMANCE COMPUTING; LOCAL OPTIMIZATIONS; MATHEMATICA; MULTI-OBJECTIVE GAMES; MULTIPLE OBJECTIVES; NASH EQUILIBRIA; NELDER-MEADE ALGORITHM; NONLINEAR PROGRAMMING PROBLEM; OPTIMIZATION PACKAGES; OPTIMIZATION PROBLEMS; SINGLE OBJECTIVE; STOCHASTIC SEARCH ALGORITHMS;

COMPUTER SCIENCE; COMPUTER SOFTWARE SELECTION AND EVALUATION; LEARNING ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; NONLINEAR PROGRAMMING;

GENETIC ALGORITHMS;

EID: 79958741074     PISSN: 17924863     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. J.F. Bard. Practical Bilevel Optimization: Algorithms and Applications. Kluwer Academic Publishers, Boston-Dordrecht-London, 1998.
2. M.G. Bengtsson. Genetic algorithms. Mathematica 2.2 notebook, National Defense Research Establishment, Linkoping, Sweden, 1993. http://library.wolfram. com/.../MathSource/569/.
3. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, Cambridge, UK-New York-Melbourne-Cape Town, 2004.
4. D. Bunnag and M. Sun. Genetic algorithm for constrained global optimization. Appl. Math. Comput., 171:604-636, 2005. (Pubitemid 41742126)
5. R. Chelouah and P. Siarry. Genetic and Nelder-Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions. European J. Oper. Res., 148:335-348, 2003.
6. Y.-W. Chen. An alternative approach to the matrix non-cooperative game with fuzzy multiple objectives. J. Chin. Inst. Ind. Eng., 19(5):9-16, 2002. (Pubitemid 41283676)
7. K. Deb. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, Chichester-New York-Weinheim, 2001.
8. N. Durand and J-M. Alliot. A combined Nelder-Mead simplex and genetic algorithm. Orlando, Florida, 1999. Genetic and Evolutionary Computation Conference. Available from: http://www.recherche.enac.fr/opti/papers/articles.
9. J. A. Freeman. Simulating Neural Networks with Mathematica. Addison-Wesley, Reading, Mass.-Menlo Park, Cal.-New York, 1994.
10. C. Geiger and C. Kanzow. Theorie und Numerik restringierter Optimierungsaufgaben. Springer Verlag, Berlin-Heidelberg-New York, 2000.
11. M. Gen and R. Cheng. Genetic Algorithms & Engineering Optimization. John Wiley & Sons, New York-Chichester-Toronto, 2000.
12. D.E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Publishing Co, Reading, MA-Menlo Park, Cal.-Sydney-Tokyo, 1989.
13. C. Jacob. Illustrating Evolutionary Computation with Mathematica. Academic Press, San Diego, CA, 2001.
14. A.A. Keller. Fuzzy multi-objective optimization modeling with mathematica. WSEAS Trans. Syst., 8(3):368-378, 2009.
15. A.A. Keller. Fuzzy multiobjective bimatrix game: introduction to the computational techniques. In N.E. Mastorakis, M. Demiralp, V. Mladenov, and Z. Boikovic, editors, Recent Advances in System Theory & Scientific Computation, Mathematics and Computers in Science and Engineering, pages 148-156, Moscow, Russia, August 2009. WSEAS, WSEAS Press.
16. N.E. Mastorakis. Solving non-linear equations via genetic algorithms. pages 24-28, Lisbon, Portugal, June 16-18 2005. Proceedings of the 6th WSEAS Inter. Conf. on Evolutionary Computing.
17. Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer, Berlin-Heidelberg-New York, 1999.
18. Z. Michalewicz and D.B. Fogel. How to Solve It: Modern Heuristics, 2nd edition. Springer, Berlin-Heidelberg-New York, 2004.
19. Z. Michalewicz and M. Schoenauer. Evolutionary algorithms for constrained parameter optimization problems. Evolutionary Computation, 1(4):1-32, 1996. (Pubitemid 126707158)
20. I. Nishizaki and M. Sakawa. Fuzzy and Multiob-jective Games for Conflict Resolution. Physica-Verlag, Springer, Heidelberg, 2001.
21. M. Sakawa. Large Scale Interactive Fuzzy Multiobjective Programming. Physica-Verlag, Springer, Heidelberg-New York, 2000.
22. M. Sakawa. Genetic Algorithms and Fuzzy Multiobjective Optimization. Kluwer Academic Publishers, Boston-Dordrecht-London, 2002.
23. M. Sakawa and I. Nishizaki. Cooperative and Noncooperative Multi-Level Programming. Operations research - Computer Science Interfaces. Springer Science+ Business Media, Dordrecht-Heidelberg-London-New York, 2009.
24. K.-B. Sim and J.-Y. Kim. Solution of multi-objective optimization problems: coevolutionary algorithm based on evolutionary game theory. Artif. Life Robotics, 8:174-185, 2004.