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http://dx.doi.org/10.11627/jkise.2013.36.3.63

Particle Swarm Optimizations to Solve Multi-Valued Discrete Problems  

Yim, Dong-Soon (Department of Industrial and Management Engineering, Hannam University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.36, no.3, 2013 , pp. 63-70 More about this Journal
Abstract
Many real world optimization problems are discrete and multi-valued. Meta heuristics including Genetic Algorithm and Particle Swarm Optimization have been effectively used to solve these multi-valued optimization problems. However, extensive comparative study on the performance of these algorithms is still required. In this study, performance of these algorithms is evaluated with multi-modal and multi-dimensional test functions. From the experimental results, it is shown that Discrete Particle Swarm Optimization (DPSO) provides better and more reliable solutions among the considered algorithms. Also, additional experiments shows that solution quality of DPSO is not lowered significantly when bit size representing a solution increases. It means that bit representation of multi-valued discrete numbers provides reliable solutions instead of becoming barrier to performance of DPSO.
Keywords
Multi-valued Discrete Problem; Genetic Algorithm; Particle Swarm Optimization;
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Times Cited By KSCI : 2  (Citation Analysis)
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