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Optimal Population Size for Genetic Algorithm Using Fuzzy System | ||
| basrah journal of science | ||
| Article 1, Volume 25, Issue 2, 2007, Pages 66-77 PDF (0 K) | ||
| Author | ||
| Emad S. Jabber | ||
| Abstract | ||
| A genetic algorithm (GA) uses the idea of biological evolution to seek good solutions to problems with very large search spaces. It has the following parameters: population size, crossover rate, and mutation rate. The selection of the initial parameters for a GA is very difficult. Some attempts to find optimal combination of parameters used trial and error methods or combination approaches, while others used a GA to find optimal parameters for another GA. The current work uses fuzzy system to determine optimal population size for any problem which is used the Genetic Algorithm. Two combinatorial problems with a large search space are used to test the effectiveness of the current work. The results are validated and GA is shown to be effective for the tested problems | ||
| Keywords | ||
| genetic algorithm; adaptive GA; adaptive crossover; traveling salesman problem; knapsack problem | ||
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