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决策变量分组优化的多目标萤火虫算法

邢文来 吴润秀 肖人彬 钟劲文 赵嘉

智能系统学报2025,Vol.20Issue(4):838-857,20.
智能系统学报2025,Vol.20Issue(4):838-857,20.DOI:10.11992/tis.202406005

决策变量分组优化的多目标萤火虫算法

A multi-objective firefly algorithm with group optimization of decision variables

邢文来 1吴润秀 1肖人彬 2钟劲文 1赵嘉1

作者信息

  • 1. 江西水利电力大学信息工程学院,江西南昌 330099||江西省水利大数据智能处理与预警技术工程研究中心,江西南昌,330099||南昌市智慧城市物联感知与协同计算重点实验室,江西南昌 330099
  • 2. 华中科技大学人工智能与自动化学院,湖北武汉 430074
  • 折叠

摘要

Abstract

Multi-objective firefly algorithm adopts an overall dimension update strategy,which often results in slow convergence and poor optimization accuracy due to inadequate optimization effects on certain dimensions.To address these problems,this paper proposes a multi-objective firefly algorithm with group optimization of decision variables(MOFA-GD).Firstly,it introduces a decision variable grouping mechanism,dividing the entire set of decision variables into a convergence variable group and a diversity variable group based on different impacts of each variable on the algorithm's performance.Secondly,it designs a decision variable grouping optimization model,utilizing learning be-havior to optimize the convergence variable group to accelerate the population's convergence speed,while using a non-uniform mutation operator to optimize the diversity variable group to prevent premature convergence.A gradually de-creasing mutation amplitude guides local exploitation by the population,thereby enhancing the algorithm's optimization accuracy.Finally,it adopts an archive truncation strategy to maintain the external archive,accurately removing crowded individuals to preserve diversity of the external archive.Experimental results show that MOFA-GD demonstrates excel-lent convergence speed and optimization accuracy,achieving a uniformly distributed Pareto optimal solution set.The proposed algorithm provides a high-efficiency and reliable solution for solving multi-objective optimization problems.

关键词

多目标优化问题/多目标萤火虫算法/变量分组/学习行为/变异算子/档案截断/收敛速度/寻优精度

Key words

multi-objective optimization problems/multi-objective firefly algorithm/variable grouping/learning beha-viour/mutation operator/archive truncation/convergence speed/optimization accuracy

分类

信息技术与安全科学

引用本文复制引用

邢文来,吴润秀,肖人彬,钟劲文,赵嘉..决策变量分组优化的多目标萤火虫算法[J].智能系统学报,2025,20(4):838-857,20.

基金项目

国家自然科学基金项目(62466037) (62466037)

南昌市重大科技攻关项目(2024zdxm002,2024zdxm010). (2024zdxm002,2024zdxm010)

智能系统学报

OA北大核心

1673-4785

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