Title: Unconstrained optimisation through bat algorithm

Authors: Shruti Goel; Nishant Goel; Divya Gupta

Addresses: Department of Computer Science, Maharaja Surajmal Institute of Technology, Guru Gobind Singh Indraprastha University, Delhi 110058, India ' Department of Computer Science, Maharaja Surajmal Institute of Technology, Guru Gobind Singh Indraprastha University, Delhi 110058, India ' Department of Computer Science, Maharaja Surajmal Institute of Technology, Guru Gobind Singh Indraprastha University, Delhi 110058, India

Abstract: Swarm-based metaheuristic algorithms have bridged the gap from ideal situation to reality. They have been successful in removing the limitations of conventional methods by providing optimal and sub-optimal solutions to those optimisation problems which were earlier considered next to impossible. Their characteristics such as self-organisation and decentralisation have led to these advancements in literature. In this paper, the performance of one such nature inspired algorithm namely the bat algorithm has been tabulated on the basis of precision and convergence speed. The conclusions drawn from the performance and observations are also described later.

Keywords: bat algorithm; unconstrained optimisation; swarm intelligence; benchmark functions; metaheuristics; precision; convergence speed.

DOI: 10.1504/IJIEI.2014.067162

International Journal of Intelligent Engineering Informatics, 2014 Vol.2 No.4, pp.259 - 270

Received: 23 Jul 2013
Accepted: 14 Apr 2014
Published online: 07 Feb 2015 *

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