Title: Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems
Authors: Gai-Ge Wang; Suash Deb; Leandro Dos Santos Coelho
Addresses: Department of Computer Science and Technology, Ocean University of China, 266100 Qingdao, China; Institute of Algorithm and Big Data Analysis, Northeast Normal University, Changchun, 130117, China; School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130117, China ' Cambridge Institute of Technology, Cambridge Village, Tatisilwai, Ranchi 835103, Jharkhand, India ' Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Parana (PUCPR), Curitiba, Parana, Brazil; Electrical Engineering Graduate Program (PPGEE), Department of Electrical Engineering, Polytechnic Center, Federal University of Parana (UFPR), Curitiba, Parana, Brazil
Abstract: 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.
Keywords: earthworm optimisation algorithm; EWA; evolutionary computation; benchmark functions; improved crossover operator; Cauchy mutation; CM; bio-inspired metaheuristic; global optimisation; swarm intelligence; evolutionary algorithms.
International Journal of Bio-Inspired Computation, 2018 Vol.12 No.1, pp.1 - 22
Received: 13 Jul 2015
Accepted: 25 Sep 2015
Published online: 29 Jun 2018 *