Improved differential evolution with dynamic mutation parameters

被引：4
作者：
Lin, Yifeng [1 ]
Yang, Yuer [1 ]
Zhang, Yinyan [1 ,2 ]
机构：
[1] Jinan Univ, Coll Cyber Secur, Guangzhou 511436, Peoples R China
[2] Pazhou Lab, Guangzhou, Peoples R China
来源：
SOFT COMPUTING | 2023年 / 27卷 / 23期
基金：
中国国家自然科学基金;
关键词：
Differential evolution (DE) Algorithm; Global optimization; Scheme optimization; Test function; ALGORITHM; OPTIMIZATION;
D O I：
10.1007/s00500-023-09080-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Differential evolution (DE) algorithms tend to be limited to local optimization when solving complex optimization problems. Different iteration schemes lead to different convergence speeds. In this paper, we mainly use the dynamic mutation parameter FS to improve the DE algorithm. Based on two ideas, a total of seven DE schemes are proposed to optimize the DE algorithm. We test the performance of the improved DE scheme on 56 test functions. Experiments show that the improved DE algorithm is better than the baseline DE algorithm in terms of accuracy, convergence and8 convergence speed.
引用
收藏
页码：17923 / 17941
页数：19
相关论文
共 40 条
  • [1] A Review of the Modification Strategies of the Nature Inspired Algorithms for Feature Selection Problem
    Abu Khurma, Ruba
    Aljarah, Ibrahim
    Sharieh, Ahmad
    Abd Elaziz, Mohamed
    Damasevicius, Robertas
    Krilavicius, Tomas
    [J]. MATHEMATICS, 2022, 10 (03)
  • [2] AN EVOLUTIONARY ALGORITHM THAT CONSTRUCTS RECURRENT NEURAL NETWORKS
    ANGELINE, PJ
    SAUNDERS, GM
    POLLACK, JB
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1994, 5 (01): : 54 - 65
  • [3] Multiguiders and Nondominate Ranking Differential Evolution Algorithm for Multiobjective Global Optimization of Electromagnetic Problems
    Baatar, Nyambayar
    Minh-Trien Pham
    Koh, Chang-Seop
    [J]. IEEE TRANSACTIONS ON MAGNETICS, 2013, 49 (05) : 2105 - 2108
  • [4] A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation
    Bhandari, Ashish Kumar
    [J]. NEURAL COMPUTING & APPLICATIONS, 2020, 32 (09) : 4583 - 4613
  • [5] Bound constraints handling in Differential Evolution: An experimental study
    Biedrzycki, Rafal
    Arabas, Jaroslaw
    Jagodzinski, Dariusz
    [J]. SWARM AND EVOLUTIONARY COMPUTATION, 2019, 50
  • [6] A hybrid recommendation system with many-objective evolutionary algorithm
    Cai, Xingjuan
    Hu, Zhaoming
    Zhao, Peng
    Zhang, WenSheng
    Chen, Jinjun
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2020, 159
  • [7] Two-Phase Differential Evolution for the Multiobjective Optimization of Time-Cost Tradeoffs in Resource-Constrained Construction Projects
    Cheng, Min-Yuan
    Duc-Hoc Tran
    [J]. IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2014, 61 (03) : 450 - 461
  • [8] Optimization of antenna configuration with a fitness-adaptive differential evolution algorithm
    Chowdhury A.
    Ghosh A.
    Giri R.
    Das S.
    [J]. Progress In Electromagnetics Research B, 2010, (26): : 291 - 319
  • [9] Novel Gamma Differential Evolution Approach for Multiobjective Transformer Design Optimization
    Coelho, Leandro dos Santos
    Mariani, Viviana Cocco
    Ferreira da Luz, Mauricio V.
    Leite, Jean Vianei
    [J]. IEEE TRANSACTIONS ON MAGNETICS, 2013, 49 (05) : 2121 - 2124
  • [10] A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training
    Cui, Runpeng
    Liu, Hu
    Zhang, Changshui
    [J]. IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 21 (07) : 1880 - 1891
1234