文章基本信息

标题：Improved symbiotic organisms search algorithm for solving unconstrained function optimization
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作者：Nama, S. ; Saha, A. ; Ghosh, S. 等
期刊名称：Decision Science Letters
印刷版ISSN：1929-5804
电子版ISSN：1929-5812
出版年度：2016
卷号：5
期号：3
页码：361-380
DOI：10.5267/j.dsl.2016.2.004
语种：English
出版社：Growing Science Publishing Company
摘要：Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (I-SOS) algorithm for solving different complex unconstrained global optimization problems. In the improved algorithm, a random weighted reflective parameter and predation phase are suggested to enhance the performance of the algorithm. The performances of this algorithm are compared with the other state-of-the-art algorithms. The parametric study of the common control parameter has also been performed.
关键词：Population based algorithm;Random weighed reflection;Random weighted difference vector;Symbiotic organisms search;Unconstrained optimization