Title: Analysis of takeover time and convergence rate for harmony search with novel selection methods
Authors: Iyad Abu Doush; Mohammed Azmi Al-Betar; Ahamad Tajudin Khader; Mohammed A. Awadallah; Ashraf Bany Mohammed
Addresses: Department of Computer Sciences, Information Technology College, Yarmouk University, 21163, Irbid, Jordan ' School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia; Department of Computer Sciences, Alhuson College, 50, Irbid, Jordan ' School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia ' School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia ' Management Information Systems Department, University of Hail, P.O. Box 2440 Hail 81451, Saudia Arabia
Abstract: Recently, common selection schemes used in harmony search algorithm (HSA) are altered in memory consideration operation to imitate the natural selection principle of survival of the fittest. The selection schemes adopted include: random, proportional, tournament, and linear rank. In this paper, these selection schemes are analysed in order to evaluate their effect on the performance of HSA. The analysis considers takeover time and convergence rate to measure the effectiveness of each selection scheme. Furthermore, a scaled proportional selection scheme is proposed to replace the proportional selection scheme to overcome its shortcoming with negative fitness values. To study the effect of these different selection schemes we use eight global optimisation functions with different characteristics. An experimental evaluation shows that linear rank selection provides the highest convergence speed and highest takeover time. On the other hand, scaled proportional selection provides the slowest convergence speed and slowest takeover time. This indicates the effect of the type of the selection method used in memory consideration in takeover time and convergence rate.
Keywords: harmony search algorithm; HSA; evolutionary algorithms; selection mechanisms; metaheuristics; takeover time; convergence rate; natural selection; global optimisation.
International Journal of Mathematical Modelling and Numerical Optimisation, 2013 Vol.4 No.4, pp.305 - 322
Received: 23 Apr 2013
Accepted: 14 Jul 2013
Published online: 26 Jul 2014 *