Evolutionary computation with simulated annealing: conditions for optimal equilibrium distribution


  • Enrique C. Segura Department of Computer Science, University of Buenos Aires, Buenos Aires, Argentina


evolutionary computation, simulated annealing, thermodynamics of equilibrium, detailed balance, ergodicity


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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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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