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Evolutionary computation with simulated annealing: conditions for optimal equilibrium distribution
Keywords:
evolutionary computation, simulated annealing, thermodynamics of equilibrium, detailed balance, ergodicityAbstract
In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function.
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References
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[2] Baeck, T., Fogel, D. B. and Michalewicz, Z.: Evolutionary Computation, two vols., London, Institute of Physics (2000).
[3] Baeck, T., Hoffmeister, F. and Schwefel, H.-P.: A Survey of Evolution Strategies. Proc. Fourth Int. Conf. Genetic Algorithms, San Mateo, Morgan Kaufmann Publishers (1991) 2-9.
[4] Baeck, T. and Schwefel, H.-P.: An overview of Evolutionary Algorithms for parameter optimization. Evolutionary Computation 1 (1), (1993) 1-23.
[5] Davis, R. and Principe: A Markov Chain Analysis of the Genetic Algorithm. Evolutionary Computation 1(3) (1993) 269-288.
[6] Eiben, A. E., Smith, J. E., Eiben, Agoston E. and Smith, J. D.: Introduction to Evolutionary Computing, Springer (2003).
[7] Goertzel, Ben. Chaotic Logic: Language, Thought and Reality from the Perspective of Complex Systems Science. New York: Plenum (1994).
[8] Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. 3rd edn. Springer-Verlag, Berlin Heidelberg New York (1996).
[9] Mitra, D., F. Romeo and A. Sangiovanni- Vincentelli: Convergence and Finite Time Behavior of Simulated Annealing. Adv. Appl. Prob. 18 (1986) 747-771.
[10]Rechenberg, I.:Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Stuttgart, Frommann-Holzboog Verlag (1973)
[11] Salamon, P., Sibani, P. and Frost, R.: Facts, Conjectures, and Improvements for Simulated Annealing, Siam Monographs on Mathematical Modeling and Computation (2002).
[12] Schwefel, H.-P.: Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie. Interdisciplinary Systems Research; 26. Basel: Birkhauser (1977).
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Published
2005-12-01
How to Cite
Segura, E. C. (2005). Evolutionary computation with simulated annealing: conditions for optimal equilibrium distribution. Journal of Computer Science and Technology, 5(04), p. 178–182. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/833
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