基于自适应嵌套粒子群算法的防空部署优化模型设计

Weijie Zhong, Xiaobing Li, Hao-Tian Chang, Fei Liang
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引用次数: 0

摘要

随着空中打击武器的快速发展,防空作战面临着越来越严峻的挑战。科学有效地部署防空力量已成为防空作战中的重要问题。本文从防空作战中敌我双方的角度,全面分析了影响防空部署的主要因素,并对战争博弈过程进行了量化。设计了一种求解空袭武器最小杀伤路径的自适应粒子群优化算法,并将其嵌入到外部粒子群优化算法的适应度函数中,设计了基于自适应嵌套粒子群优化算法的防空部署模型。仿真实例证明了该模型的可行性和有效性,可为防空部署作战决策问题的研究提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of air defense deployment optimization model based on adaptive nested PSO algorithm
With the rapid development of air strike weapons, air defense operations are facing increasingly severe challenges. Deploying air defenses scientifically and effectively has become an important issue in air defense operations. This paper comprehensively analyzes the main factors affecting air defense deployment from the perspective of both sides of the enemy and us in air defense operations, and quantifies the process of the war game. An adaptive particle swarm optimization algorithm is designed to solve the minimum kill path of air strike weapons, and it is embedded in the fitness function of the outer particle swarm optimization algorithm, and an air defense deployment model based on the adaptive nested particle swarm optimization algorithm is designed. The simulation example proves that the model is feasible and effective, and can provide reference for the research of air defense deployment combat decision-making problems.
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