系统工程与电子技术

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基于分解进化多目标优化算法的火力分配问题

张滢, 杨任农, 左家亮, 景小宁   

  1. (空军工程大学航空航天工程学院, 陕西 西安 710038)
  • 出版日期:2014-12-08 发布日期:2010-01-03

Weapontarget assignment based on decompositionbased evolutionary#br# multiobjective optimization algorithms

ZHANG Ying, YANG Rennong, ZUO Jialiang, JING Xiaoning   

  1. (College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi’an 710038, China)
  • Online:2014-12-08 Published:2010-01-03

摘要:

战前制定合理的火力分配方案,可以优化资源配置,用最小的代价获取最大的战场收益。综合考虑攻击、资源和毁伤概率等约束条件,建立了火力分配多目标优化数学模型。提出了一种求解火力分配模型的分解进化多目标优化算法,并设计了不可行解修复方法。仿真实验得出两个结论,一是不可行解修复方法可以显著提高算法的收敛性;二是在解决火力分配优化问题上,所提算法具有较好的收敛性和分散性,采用合适的分解方法可以有效提高算法的性能。

Abstract:

Making reasonable weapontarget assignment plans before the war can optimize the allocation of limited resources,which brings maximum awards with minimum costs. By integrating the constraints of attack,resource using and kill probability, a mathematic model on weapontarget assignment is formulated. Then, a decompositionbased evolutionary multiobjective optimization algorithm,with a repair method, is proposed. Simulation results indicate two conclusions. The first is that the proposed repair method can evidently improve the convergence performance of the decompositionbased algorithms. The second is that the decompositionbased algorithms can solve weapontarget assignment with good convergence performance and spacing performance, and appropriate decomposition approaches adopted can effectively improve the performances of decompositionbased algorithms.