Authors: Bilal H. Abed-Alguni; Ahmad F. Klaib; Khalid M.O. Nahar
Addresses: Department of Computer Sciences, Yarmouk University, Irbid, Jordan ' Department of Computer Information Systems, Yarmouk University, Irbid, Jordan ' Department of Computer Sciences, Yarmouk University, Irbid, Jordan
Abstract: The whale optimisation algorithm (WOA) is a newly proposed evolutionary algorithm that uses a simulation model based on the bubble-net hunting mechanism of humpback whales to find solutions for different classes of optimisation problems. WOA may occasionally converge to suboptimal solutions because of the loss of diversity in its population of candidate solutions. The island model is a distributed approach that is commonly used to control the population diversity in evolutionary algorithms. This paper introduces an improved version of WOA namely island-based whale optimisation algorithm (iWOA) that incorporates the island model into WOA. The iWOA algorithm was compared to well-known optimisation algorithms using 18 standard benchmark functions. The simulation results indicate that iWOA improves the accuracy of results compared to WOA and other popular evolutionary algorithms. In addition, the sensitivity analysis of iWOA to its parameters indicates that its convergence behaviour is sensitive to the parameters of the island model.
Keywords: whale optimisation; island model; structured population; optimisation; evolutionary algorithm.
International Journal of Reasoning-based Intelligent Systems, 2019 Vol.11 No.4, pp.319 - 329
Received: 31 Jul 2018
Accepted: 03 Nov 2018
Published online: 08 Nov 2019 *