基于粒子群算法和遗传算法的混合进化算法

The 2003 Congress on Evolutionary Computation, 2003. CEC '03. Pub Date : 2003-12-08 DOI:10.1109/CEC.2003.1299387

Xiaohu Shi, Y. H. Lu, Chunguang Zhou, H. Lee, W. Z. Lin, Yanchun Liang

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引用次数: 95

摘要

受遗传算法思想的启发，通过对粒子群算法和遗传算法的交叉，提出了两种基于粒子群算法和遗传算法的混合进化算法。提出的两种方法的主要思想是将粒子群算法和遗传算法分别以并联和串联形式进行整合。对一系列基准测试函数的仿真表明，两种方法都比标准粒子群算法具有更好的全局寻优能力。

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Hybrid evolutionary algorithms based on PSO and GA

Inspired by the idea of genetic algorithm, we propose two hybrid evolutionary algorithms based on PSO and GA methods through crossing over the PSO and GA algorithms. The main ideas of the two proposed methods are to integrate PSO and GA methods in parallel and series forms respectively. Simulations for a series of benchmark test functions show that both of the two proposed methods possess better ability to find the global optimum than that of the standard PSO algorithm.

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来源期刊

The 2003 Congress on Evolutionary Computation, 2003. CEC '03.

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