ISPAES: Evolutionary multi-objective optimization with constraint handling

被引:0
|
作者
Aguirre, AH [1 ]
Rionda, SB [1 ]
Lizarraga, G [1 ]
Coello, CC [1 ]
机构
[1] Mineral Valenciana, Dept Comp Sci, Ctr Res Math, Guanajuato 36240, Mexico
关键词
D O I
10.1109/ENC.2003.1232913
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this article we introduce Inverted and Shrinkable Pareto Archived Evolutionary Strategies, IS-PAES, an evolutionary algorithm for multiple objective optimization with constraint handling. IS-PAES inherits from PAES the use of an adaptable grid to control diversity, but here this grid can grow and shrink dinamically until the constraints are met. We also propose a novel approach to remove unfeasible individuals from the population while keeping high population diversity. Several examples of the literature are used to show the potential of ISPAES.
引用
收藏
页码:338 / 345
页数:8
相关论文
共 50 条
  • [1] Constraint handling in multi-objective evolutionary optimization
    Woldesenbet, Yonas G.
    Tessema, Birak G.
    Yen, Gary G.
    2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 3077 - 3084
  • [2] New constraint-handling method for multi-objective and multi-constraint evolutionary optimization
    Oyama, Akira
    Shimoyama, Koji
    Fujii, Kozo
    TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2007, 50 (167) : 56 - 62
  • [3] Handling uncertainties in evolutionary multi-objective optimization
    Tan, Kay Chen
    Goh, Chi Keong
    COMPUTATIONAL INTELLIGENCE: RESEARCH FRONTIERS, 2008, 5050 : 262 - +
  • [4] Noise handling in evolutionary multi-objective optimization
    Goh, C. K.
    Tan, K. C.
    2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6, 2006, : 1339 - +
  • [5] Comparison of Constraint Handling Approaches in Multi-objective Optimization
    Chhipa, Rohan Hemansu
    Helbig, Marde
    ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2018, PT I, 2018, 10841 : 345 - 362
  • [6] An efficient constraint handling methodology for multi-objective evolutionary algorithms
    Granada Echeverri, Mauricio
    Lopez Lezama, Jesus Maria
    Romero, Ruben
    REVISTA FACULTAD DE INGENIERIA-UNIVERSIDAD DE ANTIOQUIA, 2009, (49): : 141 - 150
  • [7] Uncertainty of Constraint Function in Evolutionary Multi-objective Optimization
    Kaji, Hirotaka
    Ikeda, Kokolo
    Kita, Hajime
    2009 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-5, 2009, : 1621 - +
  • [8] Evolutionary Constrained Multi-objective Optimization using NSGA-II with Dynamic Constraint Handling
    Jiao, Ruwang
    Zeng, Sanyou
    Li, Changhe
    Pedrycz, Witold
    2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2019, : 1634 - 1641
  • [9] Handling objective preference and variable uncertainty in evolutionary multi-objective optimization
    Yadav, Deepanshu
    Ramu, Palaniappan
    Deb, Kalyanmoy
    SWARM AND EVOLUTIONARY COMPUTATION, 2025, 94
  • [10] A constraint handling technique for implementing Multi-Objective Evolutionary Neural Networks
    El Hamdi, R.
    Njah, M.
    2018 15TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS AND DEVICES (SSD), 2018, : 982 - 987