Global and local real-coded genetic algorithms based on parent-centric crossover operators

被引:217
作者
Garcia-Martinez, C. [1 ]
Lozano, M.
Herrera, F.
Molina, D.
Sanchez, A. M.
机构
[1] Univ Cordoba, Dept Comp & Numer Anal, E-14071 Cordoba, Spain
[2] Univ Granada, Dept Comp Sci & Artificial Intelligence, E-18071 Granada, Spain
[3] Univ Cadiz, Dept Software Engn, Cadiz 11002, Spain
[4] Univ Granada, Dept Software Engn, E-18071 Granada, Spain
关键词
real-coded genetic algorithms; steady-state genetic algorithms; parent selection mechanism; parent-centric crossover; operators; chromosome differentiation; hybrid real-coded genetic algorithms;
D O I
10.1016/j.ejor.2006.06.043
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Parent-centric real-parameter crossover operators create the offspring in the neighbourhood of one of the parents, the female parent. The other parent, the male one, defines the range of the neighbourhood. With the aim of improving the behaviour of these crossover operators, we present three processes that are performed before their application. First, a female and male differentiation process determines the individuals in the population that may become female or/and male parents. Then, two different selection mechanisms choose the female and male parents from each group. In addition, we tackle the election of the most adequate evolution model to take out profit from these parent selection mechanisms. The experimental results confirm that these three processes may enhance the operation of the parent-centric crossover operators. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1088 / 1113
页数:26
相关论文
共 80 条
  • [1] [Anonymous], 1991, Handbook of genetic algorithms
  • [2] Arnold DV, 2002, IEEE T EVOLUT COMPUT, V6, P30, DOI [10.1109/4235.985690, 10.1023/A:1015059928466]
  • [3] Back T., 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence (Cat. No.94TH0650-2), P57, DOI 10.1109/ICEC.1994.350042
  • [4] Back T., 1996, EVOLUTIONARY ALGORIT
  • [5] Ballester PJ, 2004, LECT NOTES COMPUT SC, V3102, P901
  • [6] Ballester PJ, 2003, LECT NOTES COMPUT SC, V2723, P706
  • [7] Incorporating chromosome differentiation in genetic algorithms
    Bandyopadhyay, S
    Pal, SK
    Maulik, U
    [J]. INFORMATION SCIENCES, 1998, 104 (3-4) : 293 - 319
  • [8] On self-adaptive features in real-parameter evolutionary algorithms
    Beyer, HG
    Deb, K
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2001, 5 (03) : 250 - 270
  • [9] Bonham CR, 1999, GECCO-99: PROCEEDINGS OF THE GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, P1491
  • [10] Branke J, 1999, GECCO-99: PROCEEDINGS OF THE GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, P68