Genetic local search with adaptive crossover probability and its application to maximum diversity problem

被引:0
|
作者
Asada H. [1 ]
Toyama F. [1 ]
Shoji K. [1 ]
Miyamichi J. [1 ]
机构
[1] Graduate School of Engineering, Utsunomiya University, Utsunomiya-city, Tochigi 321-8585, 7-1-2, Yoto
关键词
Genetic local search; Maximum diversity problem; Metaheuristics;
D O I
10.1541/ieejeiss.130.519
中图分类号
学科分类号
摘要
This paper proposes a genetic local search (GLS) with crossover probability based on the distance between parent individuals. According to the distance between two selected parent individuals, the probability of crossover is decided. This probability is varied depending on the fitness values of parents and their child. By using adaptively varying the probability, the optimal distance between two parents for crossover is estimated. The proposed method is applied to the maximum diversity problem and compared with the previous GLS. © 2010 The Institute of Electrical Engineers of Japan.
引用
收藏
页码:519 / 520
页数:1
相关论文
共 50 条
  • [21] A New Adaptive Genetic Algorithm and Its Application in the Layout problem
    Wu Lei
    Xiao Wensheng
    Wang Jingli
    Zhou Houqiang
    Tian Xue
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2015, 8 (06) : 1044 - 1052
  • [22] A New Adaptive Genetic Algorithm and Its Application in the Layout problem
    Wu Lei
    Xiao Wensheng
    Wang Jingli
    Zhou Houqiang
    Tian Xue
    International Journal of Computational Intelligence Systems, 2015, 8 : 1044 - 1052
  • [23] SCCWalk: An efficient local search algorithm and its improvements for maximum weight clique problem
    Wang, Yiyuan
    Cai, Shaowei
    Chen, Jiejiang
    Yin, Minghao
    ARTIFICIAL INTELLIGENCE, 2020, 280 (280)
  • [24] Healthcare Staff Routing Problem using Adaptive Genetic Algorithms with Adaptive Local Search and Immigrant Scheme
    Sinthamrongruk, Thepparit
    Dahal, Keshav
    Satiya, Oranut
    Vudhironarit, Thishnapha
    Yodmongkol, Pitipong
    2017 INTERNATIONAL CONFERENCE ON DIGITAL ARTS, MEDIA AND TECHNOLOGY (ICDAMT): DIGITAL ECONOMY FOR SUSTAINABLE GROWTH, 2017, : 120 - 125
  • [25] Local Search Algorithms for the Maximum Carpool Matching Problem
    Kutiel, Gilad
    Rawitz, Dror
    ALGORITHMICA, 2020, 82 (11) : 3165 - 3182
  • [26] Local search for the maximum k-plex problem
    Wayne Pullan
    Journal of Heuristics, 2021, 27 : 303 - 324
  • [27] Fast local search for the maximum independent set problem
    Andrade, Diogo V.
    Resende, Mauricio G. C.
    Werneck, Renato F.
    JOURNAL OF HEURISTICS, 2012, 18 (04) : 525 - 547
  • [28] Local Search Algorithms for the Maximum Carpool Matching Problem
    Gilad Kutiel
    Dror Rawitz
    Algorithmica, 2020, 82 : 3165 - 3182
  • [29] A Local Search Heuristic for Solving the Maximum Dispersion Problem
    Moeini, Mahdi
    Goerzen, David
    Wendt, Oliver
    INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2018, PT I, 2018, 10751 : 362 - 371
  • [30] Accelerating Local Search for the Maximum Independent Set Problem
    Dahlum, Jakob
    Lamm, Sebastian
    Sanders, Peter
    Schulz, Christian
    Strash, Darren
    Werneck, Renato F.
    EXPERIMENTAL ALGORITHMS, SEA 2016, 2016, 9685 : 118 - 133