App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 1

Multi-vector collaborative mutation parameter adaptive differential evolution algorithm

Zhao Ming1,2,3
Zhang Tingting1,2,3
Cao Yang1,2,3
Sun Huanliang1,2,3
Yuan Shuai1,2,3
1. School of Computer Science and Engineering, Shenyang Jianzhu University, Shenyang 110168, China
2. Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction, Shenyang 110168, China
3. Shenyang Branch of National Special Computer Engineering Technology Research Center, Shenyang 110168, China
DOI: 10.19734/j.issn.1001-3695.2026.05.0147

Abstract

To address drawbacks of differential evolution (DE) in complex optimization—local optima stagnation, parameter sensitivity, and exploration-exploitation imbalance—this paper proposed a multi-vector collaborative mutation parameter adaptive differential evolution algorithm (MVCM-DE) . It designed a dual-archive multi-vector mutation strategy, utilizing elite, superior, and inferior solutions to enhance exploitation while maintaining diversity. It proposed a state-aware parameter control strategy to dynamically adjust parameters based on population status. It also introduced an evaluation framework to accurately detect and address premature convergence and stagnation. Experiments evaluated MVCM-DE on 30D and 50D CEC2014 benchmark problems against six DE variants and verified its generalization on CEC2017. Results show that MVCM-DE outperforms competitors across multiple functions, ranking first in the Friedman test with superior accuracy, convergence speed, and robustness.

Foundation Support

辽宁省教育厅基本科研项目(LJ212410153017)
辽宁省教育厅重点科研项目(LJ212510153014)
辽宁省科技厅揭榜挂帅项目(2025JH2/102800005)
辽宁省科技厅自然科学基金计划项目(2023-MS-222)
国家自然科学基金资助项目(62073227)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.05.0147
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 1

Publish History

[2026-09-08] Accepted Paper

Cite This Article

赵明, 张婷婷, 曹阳, 等. 多向量协同变异的参数自适应差分进化算法 [J]. 计算机应用研究, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0147. (Zhao Ming, Zhang Tingting, Cao Yang, et al. Multi-vector collaborative mutation parameter adaptive differential evolution algorithm [J]. Application Research of Computers, 2027, 44 (1). (2026-09-14). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0147. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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