An efficient Differential Evolution based algorithm for solving multi-objective optimization problems

被引：223
|
作者：
Ali, Musrrat. [1 ]
Siarry, Patrick [1 ]
Pant, Millie. [2 ]
机构：
[1] Univ Paris Est Creteil, LiSSi, EA3956, F-94010 Creteil, France
[2] Indian Inst Technol Roorkee, Dept Paper Technol, Roorkee 247667, Uttar Pradesh, India
来源：
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2012年 / 217卷 / 02期
关键词：
Evolutionary computation; Global optimization; Multiple objective programming; Opposition-Based Learning; Random localization;
D O I：
10.1016/j.ejor.2011.09.025
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-Objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for generating an initial population of potential candidates and the concept of random localization in mutation step. Finally, it introduces a new selection mechanism for generating a well distributed Pareto optimal front. The performance of proposed algorithm is investigated on a set of nine bi-objective and five tri-objective benchmark test functions and the results are compared with some recently modified versions of DE for MOPs and some other Multi Objective Evolutionary Algorithms (MOEA5). The empirical analysis of the numerical results shows the efficiency of the proposed algorithm. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：404 / 416
页数：13
相关论文
共 50 条
  • [21] MOCBOA: Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving Engineering Design Problems
    Chalabi, Nour Elhouda
    Attia, Abdelouahab
    Almazyad, Abdulaziz S.
    Mohamed, Ali Wagdy
    Werner, Frank
    Jangir, Pradeep
    Shokouhifar, Mohammad
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2025, : 967 - 1008
  • [22] Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm
    Charayron, Remy
    Lefebvre, Thierry
    Bartoli, Nathalie
    Morlier, Joseph
    AEROSPACE SCIENCE AND TECHNOLOGY, 2023, 142
  • [23] Multi-objective optimization algorithm assisted by metamodels with applications in aerodynamics problems
    Gautier, Nelson Jose Diaz
    Manzanare Filho, Nelson
    Ramirez, Edna Raimunda da Silva
    APPLIED SOFT COMPUTING, 2022, 117
  • [24] A Novel Multi-Objective Shuffled Complex Differential Evolution Algorithm with Application to Hydrological Model Parameter Optimization
    Guo, Jun
    Zhou, Jianzhong
    Zou, Qiang
    Liu, Yi
    Song, Lixiang
    WATER RESOURCES MANAGEMENT, 2013, 27 (08) : 2923 - 2946
  • [25] An interval algorithm for multi-objective optimization
    Ruetsch, GR
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2005, 30 (01) : 27 - 37
  • [26] A hybrid differential evolution algorithm solving complex multimodal optimization problems
    You, Xuemei
    Hao, Fanchang
    Ma, Yinghong
    Journal of Information and Computational Science, 2015, 12 (13): : 5175 - 5182
  • [27] An interval algorithm for multi-objective optimization
    G.R. Ruetsch
    Structural and Multidisciplinary Optimization, 2005, 30 : 27 - 37
  • [28] Multi-objective differential evolution for truss design optimization with epistemic uncertainty
    Su, Yu
    Tang, Hesheng
    Xue, Songtao
    Li, Dawei
    ADVANCES IN STRUCTURAL ENGINEERING, 2016, 19 (09) : 1403 - 1419
  • [29] A novel differential evolution algorithm for solving constrained engineering optimization problems
    Mohamed, Ali Wagdy
    JOURNAL OF INTELLIGENT MANUFACTURING, 2018, 29 (03) : 659 - 692
  • [30] A competitive mechanism based multi-objective differential evolution algorithm and its application in feature selection
    Pan, Jeng-Shyang
    Liu, Nengxian
    Chu, Shu-Chuan
    KNOWLEDGE-BASED SYSTEMS, 2022, 245
12345