一种基于引力搜索算法的单峰优化混合算法

M. Doraghinejad, H. Nezamabadi-pour, Armindokht Hashempour Sadeghian, M. Maghfoori
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引用次数: 20

摘要

目前,启发式算法在求解优化问题中受到高度重视。这些算法的基本原理是受到大自然的启发。重力搜索算法(GSA)是一种利用重力和质量相互作用定律提出的启发式搜索算法。本文提出了一种新的算子,称为“黑洞”。这个操作者受到一种天文现象概念的启发。通过加入黑洞算子,改进了GSA的利用。采用7个标准单峰基准对算法进行了评价。实验结果表明,该算法与标准GSA算法和加入干扰算子的其他版本GSA算法相比,具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid algorithm based on gravitational search algorithm for unimodal optimization
Nowadays, utilizing heuristic algorithms is highly appreciated in solving optimization problems. The fundamental of these algorithms are inspired by nature. The gravitational search algorithm (GSA) is a novel heuristic search algorithm which is invented by using law of gravity and mass interactions. In this paper, a new operator is presented which is called “the black hole”. This operator is inspired by the concept of an astronomy phenomenon. By adding the black hole operator, the exploitation of the GSA is improved. The proposed algorithm is evaluated by seven standard unimodal benchmarks. The results obtained demonstrate better performance of the proposed algorithm in comparison with those of the standard GSA and other version of GSA which is equipped with the disruption operator.
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