Seeker optimization algorithm:a novel stochastic search algorithm for global numerical optimization

被引:0
|
作者
Chaohua Dai1
2.Department of Electronic Engineering
3.Department of Computer and Communication Engineering
机构
基金
中国国家自然科学基金;
关键词
swarm intelligence; global optimization; human searching behaviors; seeker optimization algorithm;
D O I
暂无
中图分类号
TP391.3 [检索机];
学科分类号
081203 ; 0835 ;
摘要
A novel heuristic search algorithm called seeker optimization algorithm(SOA) is proposed for the real-parameter optimization.The proposed SOA is based on simulating the act of human searching.In the SOA,search direction is based on empirical gradients by evaluating the response to the position changes,while step length is based on uncertainty reasoning by using a simple fuzzy rule.The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in comparison to differential evolution(DE) and three modified particle swarm optimization(PSO) algorithms.The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.
引用
收藏
页码:300 / 311
页数:12
相关论文
共 50 条
  • [41] A novel improved accelerated particle swarm optimization algorithm for global numerical optimization
    Wang, Gai-Ge
    Gandomi, Amir Hossein
    Yang, Xin-She
    Alavi, Amir Hossein
    [J]. ENGINEERING COMPUTATIONS, 2014, 31 (07) : 1198 - 1220
  • [42] Wingsuit Flying Search-A Novel Global Optimization Algorithm
    Covic, Nermin
    Lacevic, Bakir
    [J]. IEEE ACCESS, 2020, 8 : 53883 - 53900
  • [43] Interior search algorithm (ISA): A novel approach for global optimization
    Gandomi, Amir H.
    [J]. ISA TRANSACTIONS, 2014, 53 (04) : 1168 - 1183
  • [44] Adaptive backtracking search optimization algorithm with pattern search for numerical optimization
    Wang, Shu
    Da, Xinyu
    Li, Mudong
    Han, Tong
    [J]. JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2016, 27 (02) : 395 - 406
  • [45] Adaptive backtracking search optimization algorithm with pattern search for numerical optimization
    Shu Wang
    Xinyu Da
    Mudong Li
    Tong Han
    [J]. Journal of Systems Engineering and Electronics, 2016, 27 (02) : 395 - 406
  • [46] An immunological algorithm for global numerical optimization
    Cutello, Vincenzo
    Narzisi, Giuseppe
    Nicosia, Giuseppe
    Pavone, Mario
    [J]. ARTIFICIAL EVOLUTION, 2006, 3871 : 284 - 295
  • [47] Interval algorithm for global numerical optimization
    Zhang, Xiaowei
    Liu, Sanyang
    [J]. ENGINEERING OPTIMIZATION, 2008, 40 (09) : 849 - 868
  • [48] Hybrid Krill Herd Algorithm with Vortex Search for Global Numerical Optimization
    YANG Jian
    WAN Zhongping
    PENG Zhenhua
    [J]. Wuhan University Journal of Natural Sciences, 2020, 25 (02) : 109 - 117
  • [49] Balancing Search Direction in Cultural Algorithm for Enhanced Global Numerical Optimization
    Ali, Mostafa Z.
    Awad, Noor
    Reynolds, Robert G.
    [J]. 2014 IEEE SYMPOSIUM ON SWARM INTELLIGENCE (SIS), 2014, : 336 - 342
  • [50] An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
    Guo, Lihong
    Wang, Gai-Ge
    Wang, Heqi
    Wang, Dinan
    [J]. SCIENTIFIC WORLD JOURNAL, 2013,