文章基本信息

标题：Nature-Inspired Engineering Optimization
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作者：Kawal Jeet
期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2017
卷号：9
期号：02
页码：19-31
出版社：Engg Journals Publications
摘要：Nature has always been a source of inspiration for human beings. It is quite apparent in recent engineering and optimization problems that have found their solutions in nature-inspired algorithms. The basic steps followed by most of these algorithms are same. Difference lies in the way these basic steps are implemented. In this paper, implementation details of six recent and popular nature-inspired algorithms namely, Artificial Bee Colony Algorithm, Bat Algorithm, Black Hole Algorithm, Cuckoo Search Algorithm, Flower Pollination Algorithm and Grey Wolf Optimization Algorithm have been discussed. They are further compared on the basis of attributes such as their source of inspiration, the individuals in the population, way of selecting current best solution, ways to identify new solutions, ways to search better solutions and ways to abandon bad solutions.
关键词：Nature-Inspired Algorithm; Black Hole Algorithm; Artificial Bee Colony Algorithm; Bat Algorithm; Cuckoo Search Algorithm; Flower Pollination Algorithm; Grey Wolf Optimization Algorithm.