A Continuous Genetic Algorithm Designed for the Global Optimization of Multimodal Functions

• Baker, J.E. (1985). “Reducing Bias and Inefficiency in the Selection Algorithm.” In Proceedings of the Second International Conference on Genetic Algorithms and their Applications, New Jersey, USA.

• Battiti, R. and G. Tecchiolli. (1996). “The Continuous ReactiveTabu Search: Blending Combinatorial Optimization and Stochastic Search for Global Optimization.” Annals of Operations Research 63, 53-188.

  Google Scholar 

• Berthiau, G. and P. Siarry. (1997). “AGenetic Algorithm for Globally Minimizing Functions of Several Continuous Variables.” In Second International Conference on Metaheuristics, Sophia-Antipolis (France).

• Bilbro, G.L. and W.E. Snyder. (1991). “Optimization of Functions with Many Minima.” IEEE Transactions on Systems, Man, and Cybernetics 21(4), 840-849.

  Google Scholar 

• Chelouah, R. and P. Siarry. (1999). “Enhanced Continuous Tabu Search: An Algorithm for the Global Optimization of Multiminima Function.” In S. Voss, S. Martello, I.H. Osman, and C. Roucairol (eds.), Meta-Heuristics, Advances and Trends in Local Search Paradigms for Optimization. Kluwer Academic Publishers, Chap. 4, pp. 49-61.

• Chipperfield, A.J., P.J. Fleming, H. Pohleim, and C.M. Fonseca. (1994). “Genetic Algorithm Toolbox User's Guide.” ACSE Research Report No. 512, University of Sheffield.

• Cvijovic, D. and J. Klinowski. (1995). “Taboo Search. An Approach to the Multiple Minima Problem.” Science 667, 664-666.

  Google Scholar 

• Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.

• Holland, J.H. (1962). “Outline for Logical Theory of Adaptative Systems.” J. ACM 3, 297-314.

  Google Scholar 

• Holland, J.H. (1975). “Adaptation in Natural and Artificial Systems.” University of Michigan Press, Ann Arbor, MI, Internal Report.

  Google Scholar 

• Hu, N. (1992). “Tabu Search Method with Random Moves for Globally Optimal Design.” International Journal for Numerical Methods in Engineering 35, 1055-1070.

  Google Scholar 

• De Jong, K.A. (1975). “An Analysis of the Behavior of a Class of Genetic Adaptative Systems.” University of Michigan, Ann Arbor, MI, Ph.D. Thesis.

  Google Scholar 

• Michalewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Programs. Heidelberg: Springer-Verlag.

  Google Scholar 

• Mühlenbein, H. (1991). “Evolution in Time and Space-The Parallel Genetic Algorithm.” In Gregory J.E. Rawlins (ed.), Foundations of Genetic Algorithms. Morgan Kaufmann Publishers, pp. 316-337.

• Mühlenbein H. and D. Schlierkamp-Voosen. (1993). “Analysis of Selection, Mutation and Recombination in Genetic Algorithms.” Technical Report 93/94, GMD.

• Mühlenbein, H., M. Schomisch, and J. Born. (1991). “The Parallel Genetic Algorithm as Function Optimizer.” In Proc. of the Fourth International Conference on Genetic Algorithms. San Diego, CA, pp. 271-278.

• Reeves, C.R. (ed.). (1995). “Modern Heuristic Techniques for Combinatorial Problems.” In Advanced Topics in Computer Science. McGraw-Hill, Chap. 4.

• Siarry, P., G. Berthiau, F. Durbin, and J. Haussy. (1997). “Enhanced Simulated Annealing for Globally Minimizing Functions of Many Continuous Variables.” ACM Transactions on Mathematical Software 23(2), 209-228.

  Google Scholar 

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