摘要
针对陆军装备现地抢修任务强度大、抢修期短、力量分散的特点,提出多抢修组条件下装备战场伴随抢修的组织实施流程,并分析了多抢修组条件下装备伴随抢修决策优化问题。综合抢修任务总完成量和抢修耗时建立决策优化目标函数,以抢修时间为硬约束条件,建立了多抢修组装备伴随抢修决策优化模型。为解决高维决策空间求解难题,通过改进遗传算法确定了任务分配和抢修顺序联合决策求解方法。案例分析表明,该模型适于解决多抢修组伴随抢修任务分配和路线规划问题,求解算法具有一定的稳定性。
For the characteristics of field rush-repair of army equipment,such as high task intensity,short available time and distributed human resources,the organization and implementation procedure of battlefield accompanying rush-repair was proposed.The optimal selection and assignment of rush-repair tasks are discussed in considering multiple rush-repair teams.To solve the decision-making issue,the available repair time is taken as a hard constraint,and the objective function is brought forward according to the quantity of repaired equipment and consumed time,and then a decision-making model is built.Considering the problem brought by high dimensional decision-making space,a solving method is proposed by using genetic algorithm.The feasibility of the proposed model and the solving method was verified through case study.
作者
王少华
吕会强
董原生
张远
WANG Shaohua;Lü Huiqiang;DONG Yuansheng;ZHANG Yuan(Department of Equipment Support and Remanufacture, Army Academy of Armored Forces, Beijing 100072, China;Information Support Section, Army Equipment Department, Beijing 100072, China)
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2021年第1期192-198,共7页
Acta Armamentarii
基金
军内科研项目(2018年)。
关键词
伴随抢修
抢修顺序
决策优化
遗传算法
accompanying rush-repair
rush-repair sequence
optimal decision-making
genetic algorithm
作者简介
王少华(1986—),男,讲师,博士,E-mail:aafe77330@163.com。
