Title: Improving ABC algorithm using new search mechanisms

Authors: Seyed-Hadi Mirghaderi; Mostafa Zandieh

Addresses: Faculty of Economics, Management and Social Sciences, Department of Management, Shiraz University, P.O. Box 71946-85115, Shiraz, Iran ' Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, P.O. Box 19883-96411, GC, Tehran, Iran

Abstract: This paper analyses current search equation of the artificial bee colony (ABC) algorithm to diagnose its search method and to provide alternative methods. Although ABC algorithm is an efficient metaheuristic for some combinatorial problems, its equation generates some out-of-range solutions. Hereby, we propose two alternative mechanisms to prevent such a malfunction. The first one uses triangular distribution to restrict the search between upper and lower bound and the second utilises truncated-normal distribution. Focused study reveals the efficiency of proposed alternatives and extended study proves their superior performance in finding near-optimum solutions for 18 benchmark functions.

Keywords: ABC; artificial bee colony; search equations; triangular distribution; truncated-normal distribution; neighbourhood search; metaheuristics; benchmark function; combinatorial problems; out-of-range solution.

DOI: 10.1504/IJISTA.2017.081312

International Journal of Intelligent Systems Technologies and Applications, 2017 Vol.16 No.1, pp.14 - 31

Received: 06 May 2015
Accepted: 12 Jan 2016
Published online: 04 Jan 2017 *

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