Performance Comparison of Electromagnetism-Like Algorithms for Global Optimization
Performance Comparison of Electromagnetism-Like Algorithms for Global Optimization作者机构：Department of Information Management Yuan Ze University Chung-Li Chinese Taipei Green Energy & Environment Research Laboratories Industrial Technology Research Institute Hsinchu Chinese Taipei
出 版 物：《Applied Mathematics》 (应用数学（英文）)
年 卷 期：2012年第3卷第10期
页 面：1265-1275页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Electromagnetism-Like Algorithm Meta-Heuristics Evolutionary Algorithm Optimization
摘 要：Electromagnetism-like (EML) algorithm is a new evolutionary algorithm that bases on the electromagnetic attraction and repulsion among particles. It was originally proposed to solve optimization problems with bounded variables. Since its inception, many variants of the EML algorithm have been proposed in the literature. However, it remains unclear how to simulate the electromagnetic heuristics in an EML algorithm effectively to achieve the best performance. This study surveys and compares the EML algorithms in the literature. Furthermore, local search and perturbed point are two techniques commonly used in an EML algorithm to fine tune the solution and to help escaping from local optimums, respectively. Performance study is conducted to understand their impact on an EML algorithm.
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