计算机工程与应用2026，Vol.62Issue(10)：54-73,20.DOI:10.3778/j.issn.1002-8331.2509-0129
多目标粒子群优化算法构建策略及在军事领域的应用综述
Review of Multi-Objective Particle Swarm Optimization Algorithm Construction Strategies and Their Applications in Military Field
摘要
Abstract
Driven by the development in fields such as engineering,economics,and computer science,multi-objective particle swarm optimization algorithms,which have the ability to generate high-quality and diverse non-dominated solution sets,have garnered widespread attention.This paper reviews the concepts and current research status of multi-objective particle swarm optimization algorithms.It summarizes theoretical concepts related to multi-objective optimization and particle swarm,and innovatively proposes four types of improvement strategies for multi-objective particle swarm optimi-zation algorithms:diversity maintenance strategies,archive management techniques,hybrid algorithms,and parameter adjustment methods.Additionally,it systematically outlines the progress of their application research in the military field,and finally summaries and prospects the future research directions and military applications of multi-objective particle swarm optimization algorithms.关键词
进化算法/多目标优化/粒子群优化算法/收敛性Key words
evolutionary algorithms/multi-objective optimization/particle swarm optimization algorithm/convergence分类
信息技术与安全科学引用本文复制引用
姚奕,李青尚,张曙光,陈朝阳..多目标粒子群优化算法构建策略及在军事领域的应用综述[J].计算机工程与应用,2026,62(10):54-73,20.基金项目
国家自然科学基金(62273356,61806221) （62273356,61806221）
高层次科技创新人才自主科研项目(KYZYJKKC0024001). （KYZYJKKC0024001）
