Authors: Waqas Haider Bangyal; Jamil Ahmed; Hafiz Tayyab Rauf
Addresses: Department of Computing and Technology, Iqra University, Islamabad, Pakistan ' Department of Computing and Technology, Kohat University of Science and Technology (KUST), Kohat, Pakistan ' Department of Computer Science, University of Gujrat, Gujrat, Pakistan
Abstract: Bat algorithm (BA) has been widely used to solve the diverse kinds of optimisation problems. In accordance with the optimisation problems, balance between the two major components: exploitation and exploration, plays a significant role in meta-heuristic algorithms. Several researchers have worked on the performance for the improvement of these algorithms. BA faces one of the major issues in high dimensions. In our work, we proposed a new variant of BA by introducing the torus walk (TW-BA) to solve this issue. To improve the local search capability instead of using the standard uniform walk, torus walk is incorporated in this paper. The simulation results performed on 19 standard benchmark functions depicts the efficiency and effectiveness of TW-BA compared with the traditional BA, directional bat algorithm, particle swarm optimisation, cuckoo search, harmony search algorithm, differential evolution and genetic algorithm. The promising experimental result suggests the superiority of proposed technique.
Keywords: bat algorithm; torus walk; chaotic inertia weight; exploitation; exploration.
International Journal of Bio-Inspired Computation, 2020 Vol.15 No.1, pp.1 - 13
Received: 24 Aug 2018
Accepted: 04 Mar 2019
Published online: 10 Mar 2020 *