Maximising hypervolume for selection in multi-objective evolutionary algorithms

被引：0
|
作者：
Bradstreet, Lucas [1 ]
Barone, Luigi [1 ]
While, Lyndon [1 ]
机构：
[1] Univ Western Australia, Sch Comp Sci & Software Engn, Crawley, WA 6009, Australia
来源：
2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6 | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
When hypervolume is used as part of the selection or archiving process in a multi-objective evolutionary algorithm, the basic requirement is to choose a subset of the solutions in a non-dominated front such that the hypervolume of the subset is maximised. We describe and evaluate two algorithms to approximate this process: a greedy algorithm that assesses and eliminates solutions individually, and a local search algorithm that assesses entire subsets. We present empirical data which suggests that a hybrid approach is needed to get the best trade-off between good results and computational cost.
引用
收藏
页码：1729 / +
页数：2
相关论文
共 50 条
  • [21] Multi-objective evolutionary algorithms for structural optimization
    Coello, CAC
    Pulido, GT
    Aguirre, AH
    [J]. COMPUTATIONAL FLUID AND SOLID MECHANICS 2003, VOLS 1 AND 2, PROCEEDINGS, 2003, : 2244 - 2248
  • [22] Multi-objective evolutionary algorithms based on the summation of normalized objectives and diversified selection
    Qu, B. Y.
    Suganthan, P. N.
    [J]. INFORMATION SCIENCES, 2010, 180 (17) : 3170 - 3181
  • [23] Robustness using Multi-Objective Evolutionary Algorithms
    Gaspar-Cunha, A.
    Covas, J. A.
    [J]. APPLICATIONS OF SOFT COMPUTING: RECENT TRENDS, 2006, : 353 - +
  • [24] Performance scaling of multi-objective evolutionary algorithms
    Khare, V
    Yao, X
    Deb, K
    [J]. EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PROCEEDINGS, 2003, 2632 : 376 - 390
  • [25] Multi-objective immune evolutionary algorithms for SLAM
    Li Meiyi
    [J]. Proceedings of the 26th Chinese Control Conference, Vol 5, 2007, : 216 - 220
  • [26] Research on evolutionary multi-objective optimization algorithms
    Gong, Mao-Guo
    Jiao, Li-Cheng
    Yang, Dong-Dong
    Ma, Wen-Ping
    [J]. Ruan Jian Xue Bao/Journal of Software, 2009, 20 (02): : 271 - 289
  • [27] A diversity metric for multi-objective evolutionary algorithms
    Li, XY
    Zheng, JH
    Xue, J
    [J]. ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS, 2005, 3612 : 68 - 73
  • [28] Parallelizing Multi-objective Evolutionary Genetic Algorithms
    Shinde, G. N.
    Jagtap, Sudhir B.
    Pani, Subhendu Kumar
    [J]. WORLD CONGRESS ON ENGINEERING, WCE 2011, VOL II, 2011, : 1534 - 1537
  • [29] Parallel Library of Multi-objective Evolutionary Algorithms
    Leon, Coromoto
    Miranda, Gara
    Segredo, Eduardo
    Segura, Carlos
    [J]. PROCEEDINGS OF THE PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING, 2009, : 28 - 35
  • [30] Data Structures in Multi-Objective Evolutionary Algorithms
    Najwa Altwaijry
    Mohamed El Bachir Menai
    [J]. Journal of Computer Science and Technology, 2012, 27 : 1197 - 1210
12345