A new adaptive penalty function in the application of genetic algorithm

CAI Hai-Luan; GUO Xue-Ping

doi:10.3969/j.issn.1000-5641.2015.06.006

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CAI Hai-Luan, GUO Xue-Ping. A new adaptive penalty function in the application of genetic algorithm[J]. Journal of East China Normal University (Natural Sciences), 2015, (6): 36-45. doi: 10.3969/j.issn.1000-5641.2015.06.006

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CAI Hai-Luan, GUO Xue-Ping. A new adaptive penalty function in the application of genetic algorithm[J]. Journal of East China Normal University (Natural Sciences), 2015, (6): 36-45. doi: 10.3969/j.issn.1000-5641.2015.06.006

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A new adaptive penalty function in the application of genetic algorithm

doi: 10.3969/j.issn.1000-5641.2015.06.006

CAI Hai-Luan,
GUO Xue-Ping^,

1.
华东师范大学~~上海市核心数学与实践重点实验室, 上海 200241

Received Date: 2014-11-05
Publish Date: 2015-11-25

Abstract

Abstract

Penalty function is one of the most commonly used method in genetic algorithm (GA) to solve nonlinear constraint optimization problems. For traditional penalty functions, it is always not easy to control penalty factors. In this paper we presenta new adaptive penalty function with simpler construction and prove its convergence.Then based on this adaptive penalty function we present a new genetic algorithm, which can make populations quickly access to feasible regions and improve local search capacity of genetic algorithms. Theoretical analysis and simulation results show that this algorithm has stronger stability and better convergence but needs less parameters than other ones.

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References

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