一种基于PSO的装备战场抢修力量调度多目标决策模型

随着现代战争的破坏性的增强,装备战场抢修需求会大量增加,需要组建机动分队进行战场抢修支援。针对派遣多个机动抢修分队的情况,应当在规定时间完成抢修任务的前提下,综合考虑装备作战能力恢复、抢修耗时、费用等因素,尽量取得最好的整体抢修效益;以此为背景建立了装备战场抢修力量调度多目标决策模型,给出了一种基于实数编码的模糊学习子群多目标粒子群算法（FLSMOPSO）进行求解,同时解决了多分队任务派遣和任务排序两个问题;最后给出了实例,验证了模型的实用性和算法的有效性。

Multi-objective Decision-Making Model of BDAR Unit Scheduling Based on PSO

As modern warfare destructive enhanced,BDAR needs will be in a substantial increase.It makes us to set up mobile repair units to support the tasks.With the situation of dispatching multiplex mobile repair units,we should be considering the equipment operational capability recovery effect,repair time-consuming,cost and other factors,and try to achieve the best overall repair efficiency under the premise of completing the tasks within a predetermined time.This article established an Equipment Battlefield Repair task allocation multi-objective decision-making model in this background,and solved the model with a FLSMOPSO based on the real-coded,while addressing the two issues of the multi-units – dispatching tasks and ordering tasks.Finally,an example was given to verify practicality of the model and effectiveness of the algorithm.