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Modified Binary Particle Swarm Optimization for Multidimensional Knapsack Problem

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This paper presents a modified binary particle swarm optimization for multidimensional knapsack problem using genotype-phenotype concept and mutation operator of genetic algorithms. Computational results show that the modified binary particle swarm optimization is capable of obtaining high-quality solutions for problems of various characteristics. Computational results also show that the modified binary particle swarm optimization is superior to the original binary particle swarm optimization.
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Keywords: Modified Binary Particle Swarm Optimization; Multidimensional Knapsack Problem

Document Type: Research Article

Affiliations: 1: School of Information and Communication Convergence Engineering, Mokwon University, Daejeon, 35349, Korea 2: Department of Information and Communication Engineering, Myongji University, Gyeonggi-do, Korea

Publication date: November 1, 2016

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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