改进PSO算法的混编群兵力部署优化

计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (6): 235-237.

改进PSO算法的混编群兵力部署优化

熊哲1，许瑞明1，田丰2

1.军事科学院军事运筹分析研究所，北京 100091
2.空军工程大学导弹学院，陕西三原 713800

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2012-02-21 发布日期:2012-02-21

Improved Particle Swarm Optimization algorithm applied to hybrid force disposition optimization

XIONG Zhe1, XU Ruiming1, TIAN Feng2

1.Institute of Military Operations Research Analysis, Academy of Military Science, Beijing 100091, China
2.Missile Institute, Air Force Engineering University, Sanyuan, Shaanxi 713800, China

Received:1900-01-01 Revised:1900-01-01 Online:2012-02-21 Published:2012-02-21

摘要/Abstract

摘要： 通过对影响混编群兵力部署因素的分析，结合混编群兵力部署原则，建立了混编群兵力部署优化模型。针对该类NP难组合优化问题，提出了一种基于线形递减权重离散粒子群算法，给出了粒子的编码及其寻优操作步骤。通过设置适当的算法参数，利用Matlab编程实现对应用实例的仿真，取得了理想的兵力部署效果，为解决混编群兵力部署优化问题提供了一种新的途径。

Abstract: By analyzing the factors which influence the hybrid force disposition, an optimization model about hybrid force disposition is found according to the principle of hybrid force disposition. To this kind of NP-hard combinational optimization problem, Particle Swarm Optimization（PSO） algorithm based on linearly decreasing weight is brought forward for the optimization problem, the particles’ coding and step of algorithm optimization are given. The ideal force disposition is obtained for an example by setting the proper algorithm parameters in the software Matlab, a new way is provided for solving the hybrid force disposition problem.

熊哲1，许瑞明1，田丰2. 改进PSO算法的混编群兵力部署优化[J]. 计算机工程与应用, 2012, 48(6): 235-237.

XIONG Zhe1, XU Ruiming1, TIAN Feng2. Improved Particle Swarm Optimization algorithm applied to hybrid force disposition optimization[J]. Computer Engineering and Applications, 2012, 48(6): 235-237.