Convergence Criteria for Genetic Algorithms
β Scribed by Greenhalgh, David; Marshall, Stephen
- Book ID
- 118177529
- Publisher
- Society for Industrial and Applied Mathematics
- Year
- 2000
- Tongue
- English
- Weight
- 147 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0097-5397
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
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
The main purpose of the present paper is the study of computational aspects, ## Ε½ . and primarily the convergence rate, of genetic algorithms GAs . Despite the fact that such algorithms are widely used in practice, little is known so far about their theoretical properties, and in particular about