Authors: Bilal H. Abed-alguni; Ahmad F. Klaib
Addresses: Department of Computer Sciences, Yarmouk University, Irbid, Jordan ' Department of Computer Information Systems, Yarmouk University, Irbid, Jordan
Abstract: The whale optimisation algorithm (WOA) is an efficient optimisation algorithm inspired by the bubble-net hunting strategy of humpback whale. As any optimisation algorithm, WOA may prematurely converge to suboptimal solutions. This paper introduces a new hybrid WOA algorithm (WOABHC) that efficiently combines the WOA algorithm with the β-hill climbing algorithm (BHC) to control the diversity of the search space. The β-hill climbing algorithm is called at each iteration of WOABHC based on the probability function used in simulated annealing to reduce the number of computations required to achieve a good solution. WOABHC was tested and compared to well-known optimisation algorithms using 25 standard benchmark functions. The experimental results confirm the efficiency of the proposed method in improving the accuracy of the results compared to WOA and other well-known optimisation algorithms.
Keywords: whale optimisation; β-hill climbing search; simulated annealing; optimisation; metaheuristic.
International Journal of Computing Science and Mathematics, 2020 Vol.12 No.4, pp.350 - 363
Received: 03 Apr 2018
Accepted: 09 May 2018
Published online: 26 Jan 2021 *