An improved differential evolution algorithm for multi-objective optimization problems

被引：0
|
作者：
Yu G. [1 ]
机构：
[1] Research Institute of Information and System Computation Science, Beifang University of Nationalities, Yinchuan Ningxia
来源：
International Journal of Advancements in Computing Technology | 2011年 / 3卷 / 09期
关键词：
Differential evolution algorithm; Migration strategy; Multi-objective optimization problems; Select operator;
D O I：
10.4156/ijact.vol3.issue9.14
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, an improved multi-objective differential evolution algorithm(IDEA) is proposed for multi-objective optimization problems. In IDEA, the select operator combines the advantages of DE with the mechanisms of Pareto-based ranking and distance density, besides, a randomly migration strategy is proposed. IDEA is implemented on four classical multi-objective problems, the simulation results indicate that the proposed IDEA efficiently achieves two goals of multi-objective optimization problems: find the solutions converse to the true Pareto-front and uniform spread along the front.
引用
收藏
页码：106 / 113
页数：7
相关论文
共 50 条
  • [1] Improved multi-objective differential evolution algorithm based on a decomposition strategy for multi-objective optimization problems
    Mingwei Fan
    Jianhong Chen
    Zuanjia Xie
    Haibin Ouyang
    Steven Li
    Liqun Gao
    Scientific Reports, 12
  • [2] Improved multi-objective differential evolution algorithm based on a decomposition strategy for multi-objective optimization problems
    Fan, Mingwei
    Chen, Jianhong
    Xie, Zuanjia
    Ouyang, Haibin
    Li, Steven
    Gao, Liqun
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [3] Application of an Improved Generalized Differential Evolution Algorithm to Multi-objective Optimization Problems
    Ramesh, Subramanian
    Kannan, Subramanian
    Baskar, Subramanian
    SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT I, 2011, 7076 : 77 - +
  • [4] An Improved Differential Evolution for Constrained Multi-objective Optimization Problems
    Song, Erping
    Li, Hecheng
    Wanma, Cuo
    2020 16TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS 2020), 2020, : 269 - 273
  • [5] Multi-objective optimization based on improved differential evolution algorithm
    Wang, Shuqiang, 1600, Universitas Ahmad Dahlan (12):
  • [6] A modified differential evolution algorithm for multi-objective optimization problems
    Tang Ke-zong
    Sun Ting-kai
    Yang Jing-yu
    Gao Shang
    PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATTERN RECOGNITION AND THE FIRST CJK JOINT WORKSHOP ON PATTERN RECOGNITION, VOLS 1 AND 2, 2009, : 15 - +
  • [7] An Improved Multi-objective Differential Evolution Algorithm
    Niu, Dapeng
    Wang, Fuli
    Chang, Yuqing
    He, Dakuo
    Gu, Dehao
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : 879 - 882
  • [8] Multi-objective optimization for economic emission dispatch using an improved multi-objective binary differential evolution algorithm
    Di, Yijuan
    Fei, Minrui
    Wang, Ling
    Wu, Wei
    INTERNATIONAL CONFERENCE ON APPLIED ENERGY, ICAE2014, 2014, 61 : 2016 - 2021
  • [9] An efficient Differential Evolution based algorithm for solving multi-objective optimization problems
    Ali, Musrrat.
    Siarry, Patrick
    Pant, Millie.
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 217 (02) : 404 - 416
  • [10] Multi-objective memetic differential evolution optimization algorithm for text clustering problems
    Mustafa, Hossam M. J.
    Ayob, Masri
    Shehadeh, Hisham A.
    Abu-Taleb, Sawsan
    NEURAL COMPUTING & APPLICATIONS, 2023, 35 (02): : 1711 - 1731
12345