Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 41, Issue 13, Pages 5788-5803Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.03.016
Keywords
Harmony search; Global-best harmony search; Periodic and sign function; Exploration and exploitation; Opposition-based learning; Numerical optimization
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Funding
- National Natural Science Foundation of China [61064012, 61164003, 61364026]
- Youth Science Foundation of Lanzhou Jiaotong University [2012029]
- Science and Technology Foundation of Lanzhou Jiaotong University [ZC2012005]
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In this paper, an improved global-best harmony search algorithm, named IGHS, is proposed. In the IGHS algorithm, initialization based on opposition-based learning for improving the solution quality of the initial harmony memory, a new improvisation scheme based on differential evolution for enhancing the local search ability, a modified random consideration based on artificial bee colony algorithm for reducing randomness of the global-best harmony search (GHS) algorithm, as well as two perturbation schemes for avoiding premature convergence, are integrated. In addition, two parameters of IGHS, harmony memory consideration rate and pitch adjusting rate, are dynamically updated based on a composite function composed of a linear time-varying function, a periodic function and a sign function in view of approximate periodicity of evolution in nature. Experimental results tested on twenty-eight benchmark functions indicate that IGHS is far better than basic harmony search (HS) algorithm and GHS. In further study, IGHS has also been compared with other eight well known metaheuristics. The results show that IGHS is better than or at least similar to those approaches on most of test functions. (C) 2014 Elsevier Ltd. All rights reserved.
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