NDLI: DSMOPSO: A distance sorting based multiobjective particle swarm optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Li Zhongkai Zhu Zhencai Zhang Huiqin
Copyright Year	2010
Description	Author affiliation: School of Foreign Languages and Culture, China University of Mining and Technology, Xuzhou, China (Zhang Huiqin) \|\| School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, China (Li Zhongkai; Zhu Zhencai)
Abstract	Aiming at shortcomings in global searching capacity and diversity of Pareto set existing in the traditional MOPSO, a crowding distance sorting based multiobjective particle swarm optimization algorithm (DSMOPSO) is proposed. With the elitism strategy, the evolution of the external population is achieved based on individuals' crowding distance sorting by descending order, to delete the redundant individuals in the crowding area. The update of the global optimum is performed by selecting an individual with a relatively bigger crowding distance, to lead the particles evolving to the disperse region. A small ratio mutation is introduced to the inner swarm to enhance the global searching capacity. So the number of Pareto optimal solutions can be controlled, and the convergence and diversity of Pareto optimal set can be guaranteed as well. Effectiveness of the algorithm with two and three objectives is proved by the optimization of three standard test problems. Comparison results illustrate that it outperformed NSGA-II and SPEA2 in the convergence and diversity characteristics of Pareto optimal front. The sensitivity of control parameters is analyzed to illustrate the algorithm's robustness.
Starting Page	2749
Ending Page	2753
File Size	365378
Page Count	5
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5582682
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis test problems multiobjective particle swarm optimization algorithm crowding distance sorting Educational institutions Particle swarm optimization elitism strategy Optimization Convergence Sorting
Content Type	Text
Resource Type	Article

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