Genetic algorithms using SISAL parallel programming language
Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.
- Research Organization:
- Lawrence Livermore National Lab., CA (United States)
- OSTI ID:
- 105141
- Report Number(s):
- UCRL-ID--114972-2; CONF-9405328--Absts.; ON: DE95014118
- Country of Publication:
- United States
- Language:
- English
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