New directional bat algorithm for continuous optimization problems

Chakri, Asma and Khelif, Rabia and Benouaret, Mohamed and Yang, Xin-She (2017) New directional bat algorithm for continuous optimization problems. Expert Systems with Applications, 69 . pp. 159-175. ISSN 0957-4174

[img] PDF - Final accepted version (with author's formatting)
Available under License Creative Commons Attribution-NonCommercial-NoDerivatives.

Download (1MB)

Abstract

Bat algorithm (BA) is a recent optimization algorithm based on swarm intelligence and inspiration from the echolocation behavior of bats. One of the issues in the standard bat algorithm is the premature convergence that can occur due to the low exploration ability of the algorithm under some conditions. To overcome this deficiency, directional echolocation is introduced to the standard bat algorithm to enhance its exploration and exploitation capabilities. In addition to such directional echolocation, three other improvements have been embedded into the standard bat algorithm to enhance its performance. The new proposed approach, namely the directional Bat Algorithm (dBA), has been then tested using several standard and non-standard benchmarks from the CEC’2005 benchmark suite. The performance of dBA has been compared with ten other algorithms and BA variants using non-parametric statistical tests. The statistical test results show the superiority of the directional bat algorithm.

Item Type: Article
Additional Information: Available online 21 October 2016
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 20804
Useful Links:
Depositing User: Xin-She Yang
Date Deposited: 25 Oct 2016 10:03
Last Modified: 07 Dec 2018 08:22
URI: http://eprints.mdx.ac.uk/id/eprint/20804

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year