一种新的具有提升选择算子的高效遗传算法

Jun-Chuan Chen, Min Cao, Zhi-hui Zhan, Dong Liu, Jun Zhang
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引用次数: 1

摘要

遗传算法是一种应用广泛的概率搜索优化算法。在遗传算法中,选择算子是保证解质量的重要算子。因此,选择算子的行为对算法的性能有很大的影响。本文基于促销竞争的思想,设计了一种新的高效的遗传算法选择算子。该算子模拟了促进竞争的规则和过程,以保护表现良好的染色体,淘汰表现较差的染色体。这是遗传算法中一个基本但重要的研究问题,它可以被用于任何现有的遗传算法变体中,以取代任何其他选择算子。我们设计了四种类型的实验来全面验证所提出的提升选择算子的行为,并将其与其他五种现有和常用的选择算子进行比较。结果表明,提升选择算子在提高遗传算法的解质量、收敛速度和运行时间方面都有较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New and Efficient Genetic Algorithm with Promotion Selection Operator
Genetic algorithm (GA) is a widely used probabilistic search optimization algorithm. In the GA, selection is an important operator to guarantee the quality of solution. Therefore, the behavior of selection operator makes a great effect on the performance of the algorithm. This paper designs a new and efficient selection operator for GA base on the idea of promotion competition. This operator simulates the rule and process of promotion competition to protect the well perform chromosomes and eliminates poor chromosomes. This is a fundamental but significant research issue in GA that may be adopted into any existing GA variants to replace any other selection operators. We design four types of experiments to comprehensively verify the behavior of the proposed promotion selection operator, by comparing it with five other existing and commonly used selection operators. The results show that promotion selection operator has a general good performance in enhancing GA in terms of solution quality, convergence speed, and running time.
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