An improved global-best harmony search algorithm for faster optimization |
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| Affiliation: | 1. Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Lembah Pantai, 50603 Kuala Lumpur, Malaysia;2. Odette School of Business, University of Windsor, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada;1. Grup de Recerca en Sistemes Intel·ligents, Ramon Llull University, Quatre Camins 2, 08022 Barcelona, Spain;2. Grup de Recerca en Internet Technologies & Storage, Ramon Llull University, Quatre Camins 2, 08022 Barcelona, Spain;3. Departamento de Ingeniería Matemática e Informática, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Spain;1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China;2. School of Software Microelectronics, Peking University, Beijing 100190, China;1. Faculty of Electronic Engineering, University of Ni?, Aleksandra Medvedeva 14, Ni?, Serbia;2. Faculty of Mechanical Engineering, University of Ni?, Aleksandra Medvedeva 14, Ni?, Serbia;1. School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China;2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton T6R 2V4 AB, Canada;3. School of Information, Liaoning University, Shenyang 110036, China |
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| Abstract: | 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. |
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| Keywords: | Harmony search Global-best harmony search Periodic and sign function Exploration and exploitation Opposition-based learning Numerical optimization |
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