资源约束的拼件维修模型与粒子群求解算法  

Resource constrained cannibalization maintenance model and solving algorithm based on particle swarm optimization

作　　者：吕学志[1,2] 于永利[1] 张柳[1] 陈乐[3] 董岳[1] 刘文武[1] 

机构地区：[1]军械工程学院装备指挥与管理系,石家庄050003 [2]总参炮兵训练基地模拟训练中心,宣化075100 [3]装备指挥技术学院装备指挥系,北京101416

出　　处：《系统工程理论与实践》2013年第4期1013-1018,共6页Systems Engineering-Theory & Practice

摘　　要：为了获得最优的装备作战单元的拼件维修方案与任务分配方案,建立了一种同时优化拼件维修方案与任务分配方案的非线性规划模型,模型中同时考虑了不同任务对武器系统的具体需求、武器系统的客观情况、维修资源约束,可以最大化地协调任务、装备群与维修资源之间的矛盾,所以更加贴合实际.设计了基于粒子群算法的求解算法,包括算法框架、粒子的表示、初始化、适应度函数、更新方法等.最后,应用该粒子群算法对具体实例进行了求解,分析表明模型与算法可以有效地优化任务分配方案与拼件维修方案,提高装备作战单元任务成功概率,为决策者制定决策提供指导.In order to get optimum solution of mission assignment and cannibalization, it puts forward a nonlinear programming model to optimize mission assignment and cannibalization solution, the factors such as mission requirements to equipment subsystem, real condition of equipment system, maintenance resource are considered in the model, the model harmonize the mission, equipment fleet and maintenance resource to the utmost, so it is more practical. It designs the solution algorithm based on particle swarm optimization （PSO）, includes algorithm framework, particle representation, initialization, fitness function and update methods. Finally, applies the algorithm to a specific example, analysis shows that the model and algorithm can optimize the mission assignment and cannibalization solution effectively and efficiently, increase the mission success probability, and provide instruction for decision maker in decision-making.

关 键 词：拼件维修策略 任务分配 维修资源 粒子群算法 

分 类 号：TP307[自动化与计算机技术—计算机系统结构]