A gradient-guided niching method in genetic algorithm for solving continuous optimisation problems

被引：0
|
作者：
Peng, JX [1 ]
Thompson, S [1 ]
Li, K [1 ]
机构：
[1] Queens Univ Belfast, Sch Mech & Mfg Engn, Belfast BT9 5AH, Antrim, North Ireland
来源：
PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4 | 2002年
关键词：
hybrid genetic algorithm; gradient search; multimodal optimisation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A hybrid genetic algorithm, which embeds a gradient-based local search route into a niching genetic algorithm, is proposed for solving continuous optimisation problems. The optimisation algorithm is applied to three nonlinear functions each having up to 100 variables and multi-minima. The test results show that relative to a standard niching algorithm the combination of a gradient-based search and niching improves the searching precision by several orders and the capability for locating the global optimum is significantly improved.
引用
收藏
页码：3333 / 3338
页数：6
相关论文
共 50 条
  • [1] A method of solving scheduling problems using improved guided genetic algorithm
    Ou, Gyouhi
    Tamura, Hiroki
    Tanno, Koichi
    Tang, Zheng
    [J]. IEEJ Transactions on Electronics, Information and Systems, 2008, 128 (08) : 1351 - 1357
  • [2] A Method of Solving Scheduling Problems Using an Improved Guided Genetic Algorithm
    Ou, Gyouhi
    Tamura, Hiroki
    Tanno, Koichi
    Tang, Zheng
    [J]. ELECTRONICS AND COMMUNICATIONS IN JAPAN, 2010, 93 (08) : 15 - 22
  • [3] Aircraft conceptual design by genetic/gradient-guided optimization
    Bos, AHW
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 1998, 11 (03) : 377 - 382
  • [4] ACORg: A Gradient-Guided ACO Algorithm for Neural Network Learning
    Abdelbar, Ashraf M.
    Salama, Khalid M.
    [J]. 2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI), 2015, : 1133 - 1140
  • [5] A chaotic artificial immune system optimisation algorithm for solving global continuous optimisation problems
    Jordehi, A. Rezaee
    [J]. NEURAL COMPUTING & APPLICATIONS, 2015, 26 (04): : 827 - 833
  • [6] A chaotic artificial immune system optimisation algorithm for solving global continuous optimisation problems
    A. Rezaee Jordehi
    [J]. Neural Computing and Applications, 2015, 26 : 827 - 833
  • [7] An Efficient Mixed Conjugate Gradient Method for Solving Unconstrained Optimisation Problems
    Mtagulwa, P.
    Kaelo, P.
    [J]. EAST ASIAN JOURNAL ON APPLIED MATHEMATICS, 2021, 11 (02) : 421 - 434
  • [8] Convergence enhanced genetic algorithm with successive zooming method for solving continuous optimization problems
    Kwon, YD
    Kwon, SB
    Jin, SB
    Kim, JY
    [J]. COMPUTERS & STRUCTURES, 2003, 81 (17) : 1715 - 1725
  • [9] Subdividing Labeling Genetic Algorithm: A New Method for Solving Continuous Nonlinear Optimization Problems
    Esmaelian, Majid
    Tavana, Madjid
    Santos-Arteaga, Francisco J.
    Vali, Masoumeh
    [J]. 2017 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2017, : 773 - 780
  • [10] Solving large processor configuration problems with the guided genetic algorithm
    Lau, TL
    Tsang, EPK
    [J]. TENTH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 1998, : 320 - 327
12345