Journal of Applied and Physical Sciences
Details
Journal ISSN: 2414-3103
Article DOI: https://doi.org/10.20474/japs-2.2.3
Received: 15 April 2016
Accepted: 23 May 2016
Published: 23 June 2016
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  • Binary Mean-Variance Mapping Optimization Algorithm (BMVMO)

Ali Hakem Al-Saeedi, Dr. Oğuz Altun

Article first published online: 2016

Abstract

Mean-Variance Mapping Optimization (MVMO) is the newest class of the modern meta-heuristic algorithms. The original version of this algorithm is suitable for continuous search problems, so can’t apply it directly to discrete search problems. In this paper, the binary version of the MVMO (BMVMO) algorithm proposed. The proposed Binary Mean-Variance Mapping Optimization algorithm compare with well-known binary meta-heuristic optimization algorithms such, Binary genetic Algorithm, Binary Particles Swarm Optimization, and Binary Bat Algorithm over fifteen benchmark functions conducted to draw a conclusion. The numeric experiments result proves that BMVMO is better performance