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OA

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.