Title: Improved bat algorithm with optimal forage strategy and random disturbance strategy

Authors: Xingjuan Cai; Xiao-zhi Gao; Yu Xue

Addresses: Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, Shanxi, 030024, China ' Department of Electrical Engineering and Automation, Aalto University, 00076, Finland ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

Abstract: Bat algorithm is a novel bio-inspired stochastic optimisation algorithm. However, due to the limited exploration and exploitation capabilities, the performance is not well when dealing with some multi-modal numerical problems. In this paper, optimal forage strategy is designed to guide the search direction for each bat and a random disturbance strategy is also employed to extend the global search pattern. To test the performance, CEC2013 benchmark test suit and four other evolutionary algorithms are employed to compare, simulation results show our modification is effective.

Keywords: bat algorithm; optimal forage strategy; random disturbance strategy; stochastic optimisation; simulation.

DOI: 10.1504/IJBIC.2016.078666

International Journal of Bio-Inspired Computation, 2016 Vol.8 No.4, pp.205 - 214

Received: 06 May 2016
Accepted: 03 Jul 2016
Published online: 30 Aug 2016 *

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