A Fuzzy Particle Swarm Approach to Multiobjective Quadratic Assignment Problems
作者： Mingyan Zhao , Ajith Abraham , Crina Grosan , Hongbo Liu , None
DOI: 10.1109/AMS.2008.169
关键词: Particle swarm optimization 、 Swarm behaviour 、 Optimization problem 、 Mathematics 、 Mathematical optimization 、 Quadratic programming 、 Fuzzy logic 、 Fuzzy set 、 Quadratic assignment problem 、 Multi-objective optimization
摘要: The multiobjective Quadratic Assignment Problem (mQAP) is considered as one of the hardest optimization problems but with many real-world applications. Since it may not be possible to simply weight importance each flow for mQAP, best use Pareto obtain front or an approximation it. Although Particle Swarm Optimization (PSO) algorithm has exhibited good performance across a wide range application problems, research on mQAP much been investigated. This paper introduces fuzzy particle swarm handle Multiobjective (mQAP). In scheme, representations position and velocity particles in conventional PSO extended from real vectors matrices. A new mapping introduced between problem space efficient way. We evaluated proposed approach. Empirical results illustrate that approach can applied solving mQAP's very effectively.
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