Evolutionary computation with simulated annealing: conditions for optimal equilibrium distribution
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...
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| Format: | Article |
| Language: | English |
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Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2005-12-01
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| Series: | Journal of Computer Science and Technology |
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| Online Access: | https://journal.info.unlp.edu.ar/JCST/article/view/833 |
| Summary: | 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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| ISSN: | 1666-6046 1666-6038 |