In this paper we consider the extension of genetic algorithms (GAs) with a probabilistic Boltzmann reduction operator and prove their convergence to the optimum. The algorithm can be seen as a hybridisation between GAs and simulated annealing (SA), i.e. a SA-like GA. The "temperature" parameter allo
Convergence of genetic algorithms
β Scribed by R. R. Sharapov; A. V. Lapshin
- Book ID
- 110209353
- Publisher
- SP MAIK Nauka/Interperiodica
- Year
- 2006
- Tongue
- English
- Weight
- 182 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1054-6618
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This paper extends genetic algorithms to achieve fast solutions to difficult problem. To accomplish this, we present empirical results on the terminated condition by bias and the functionized model of mutation rate in genetic algerithms. The terminated condition by bias enable to reducing computati
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