Computer Science ›› 2016, Vol. 43 ›› Issue (8): 262-266.doi: 10.11896/j.issn.1002-137X.2016.08.053

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Particle Swarm Algorithm for Multi-objective Optimization Based on Intuitionistic Fuzzy Entropy

SU Ding-wei, ZHOU Chuang-ming and WANG Yi   

  • Online:2018-12-01 Published:2018-12-01

Abstract: A particle swarm algorithm for multi-objective optimization problems based on intuitionistic fuzzy entropy was proposed to overcome the deficiency that the performance of algorithm’s convergence and distribution is not high.Firstly,the algorithm uses a metric based on intuitionistic fuzzy entropy to measure the diversity of the population in the case of multi-objective space.Then,three strategies,namely dynamic changes of inertia weight,use of the external archive and mutation operator mechanism based on intuitionistic fuzzy entropy,was designed and intuitionistic fuzzy multi-objective programming model was built to enhance the extent of the algorithm’s exploration,increasing the diversity of the evolving population and prevent premature convergence.At last,results of simulation indicate that the proposed algorithm has good performance of convergence and distribution,and it is useful for dealing with multi-objective optimization problems.

Key words: Intuitionistic fuzzy entropy,Particle swarm optimization,Diversity,Multi-objective optimization

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