Authors: Krishna Gopal Dhal; Sanjoy Das
Addresses: Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, West Bengal, India ' Department of Engineering and Technological Studies, University of Kalyani, Kalyani, Nadia, India
Abstract: Bat algorithm (BA) is a new metaheuristic optimisation algorithm, which has already proved its supreme performance on many optimisation fields. However, it is possible to increase its efficiency when solving complex optimisation problems. This study concentrates on improving the efficiency of BA by incorporating different types of local search strategies and novel self-adaption strategies of parameters such as loudness, pulse rate and frequency. Comparative analysis of three different proposed local search strategies has been performed to find the best one. The proposed modified BAs with local search strategies are employed to solve five popular image enhancement models. Experimental results prove that self-adaption of parameters enhances the capability of standard BA. But the addition of efficient local search technique with self-adaption increases the effectiveness of the standard BA to a great extent.
Keywords: image enhancement; bat algorithm; self-adaptive; local search; chaos; optimisation.
International Journal of Computing Science and Mathematics, 2020 Vol.11 No.1, pp.1 - 28
Received: 06 Apr 2017
Accepted: 21 Sep 2017
Published online: 27 Feb 2020 *