Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems

被引：357
|
作者：
Wang, Gai-Ge [1 ,2 ,3 ]
Deb, Suash [4 ]
Coelho, Leandro dos Santos [5 ,6 ]
机构：
[1] Ocean Univ China, Dept Comp Sci & Technol, Qingdao 266100, Peoples R China
[2] Northeast Normal Univ, Inst Algorithm & Big Data Anal, Changchun 130117, Jilin, Peoples R China
[3] Northeast Normal Univ, Sch Comp Sci & Informat Technol, Changchun 130117, Jilin, Peoples R China
[4] Cambridge Inst Technol, Ranchi 835103, Jharkhand, India
[5] Pontifical Catholic Univ Parana PUCPR, Ind & Syst Engn Grad Program PPGEPS, Curitiba, Parana, Brazil
[6] Fed Univ Parana UFPR, Polytech Ctr, Dept Elect Engn, Elect Engn Grad Program PPGEE, Curitiba, Parana, Brazil
来源：
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION | 2018年 / 12卷 / 01期
基金：
中国国家自然科学基金;
关键词：
earthworm optimisation algorithm; EWA; evolutionary computation; benchmark functions; improved crossover operator; Cauchy mutation; CM; bio-inspired metaheuristic; global optimisation; swarm intelligence; evolutionary algorithms; KRILL HERD ALGORITHM; BIOGEOGRAPHY-BASED OPTIMIZATION; PARTICLE SWARM OPTIMIZATION; ARTIFICIAL BEE COLONY; MODEL;
D O I：
10.1504/IJBIC.2015.10004283
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Earthworms can aerate the soil with their burrowing action and enrich the soil with their waste nutrients. Inspired by the earthworm contribution in nature, a new kind of bio-inspired metaheuristic algorithm, called earthworm optimisation algorithm (EWA), is proposed in this paper. The EWA method is inspired by the two kinds of reproduction (Reproduction 1 and Reproduction 2) of the earthworms. Reproduction 1 generates only one offspring by itself. Reproduction 2 is to generate one or more than one offspring at one time, and this can successfully be done by nine improved crossover operators. In addition, Cauchy mutation (CM) is added to EWA method. Nine different EWA methods with one, two and three offsprings based on nine improved crossover operators are respectively proposed. The results show that EWA23 performs the best and it can find the better fitness on most benchmarks than others.
引用
收藏
页码：1 / 22
页数：22
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