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兵工学报 ›› 2017, Vol. 38 ›› Issue (8): 1593-1602.doi: 10.3969/j.issn.1000-1093.2017.08.018

• 论文 • 上一篇    下一篇

考虑非遍历的抢修任务多目标动态调度

陈春良1, 陈伟龙1, 陈康柱2, 刘彦1, 史宪铭3   

  1. (1.装甲兵工程学院 技术保障工程系, 北京 100072; 2.装甲兵工程学院 训练部, 北京 100072;3.军械工程学院 装备指挥与管理系, 河北 石家庄 050003)
  • 收稿日期:2017-01-05 修回日期:2017-01-05 上线日期:2017-10-10
  • 作者简介:陈伟龙(1988—),男,博士研究生。E-mail:amose_chen@163.com

Multi-objective and Dynamic Scheduling of Battlefield Rush-repair Tasks Based on Non-ergodicity

CHEN Chun-liang1, CHEN Wei-long1, CHEN Kang-zhu2, LIU Yan1, SHI Xian-ming3   

  1. (1.Department of Technical Support Engineering, Academy of Armored Force Engineering, Beijing 100072, China;2.Department of Training, Academy of Armored Force Engineering,Beijing 100072, China;3.Department of Equipment Command and Management, Ordinance Engineering College,Shijiazhuang 050003, Hebei, China)
  • Received:2017-01-05 Revised:2017-01-05 Online:2017-10-10

摘要: 针对进攻作战中战损装备众多而抢修时间与抢修力量有限的矛盾,进行了进攻作战抢修任务动态调度研究。提出考虑非遍历的抢修任务多目标动态调度的现实军事问题,建立多目标规划数学模型,分析了非遍历、修理能力差异、待修装备优先级3个重要影响因素;根据所建模型的特点,设计了基于遗传算法的模型求解算法;运用Matlab软件进行了39辆待修装备、3个抢修组的动态调度示例仿真与分析。示例结果表明:通过实施机动伴随抢修和抢修任务动态调度,进攻作战部队能够获得约185 h的二次作战总时间,进而增强部队的持续作战能力,并大大减少决策工作量和决策时间、降低人为决策风险。

关键词: 兵器科学与技术, 战场抢修, 动态调度, 非遍历, 遗传算法

Abstract: In the offensive operation, equipment is constantly damaged, but the battlefield rush-repair time and power are limited. The dynamic scheduling of battlefield rush-repair tasks in the offensive operation is studied. A multi-objective and dynamic scheduling of battlefield rush-repair tasks based on non-ergodicity, which is a real military problem, is presented. A mathematical model of multi-objective programming is established. Three key factors, including non-ergodicity, repair ability difference and priority of equipment to be repaired, are analyzed. A scheduling example of 39 equipment to be repaired and 3 repair groups is simulated and analyzed by using Matlab. The simulated result shows that the proposed model is scientific and reasonable, and the algorithm is correct and efficient, which can effectively solve the difficult problem of non-ergodic optimization and dynamically track the change of the optimal solution. Key

Key words: ordnancescienceandtechnology, battlefieldrush-repair, dynamicscheduling, non-ergodicity, geneticalgorithm

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