Title: Whale optimisation algorithm based on Kent mapping and adaptive parameters
Authors: Benjia Hu; Zhiyong Wu; Wen Gao; Ke Meng; Dayin Shi; Xiuwei Hu; Yilong Sun
Addresses: School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China ' School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China ' Zibo Industrial Digital Economy Development Centre, No. 63, Liuquan Road, Zhangdian District, Zibo, 255000, China ' School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China ' School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China ' School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China ' School of Computer Science and Technology, Shandong University of Technology, Zibo, 255000, China
Abstract: Aiming at the shortcomings of whale optimisation algorithm, such as easy to fall into local optimisation and slow convergence speed in the later stage, an optimisation method based on three improved strategies is proposed. Firstly, Kent mapping is introduced to initialise the population and enrich the diversity of the population; Secondly, a nonlinear convergence factor strategy is proposed to improve the global search speed and local optimisation accuracy. Finally, inertia weight is added to maintain the balance between global search and local optimisation. Simulation experiments with 13 standard test functions show that the proposed algorithm has remarkable performance in global search, convergence speed and optimisation accuracy. In addition, through its application in path planning, the feasibility and effectiveness of the algorithm proposed in this paper are further verified.
Keywords: Kent mapping; nonlinear factor; inertia weight; whale optimisation algorithm; WOA; global optimisation; route planning.
DOI: 10.1504/IJICA.2023.134231
International Journal of Innovative Computing and Applications, 2023 Vol.14 No.4, pp.230 - 243
Received: 03 Jun 2022
Accepted: 21 Dec 2022
Published online: 13 Oct 2023 *