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兵工学报 ›› 2017, Vol. 38 ›› Issue (5): 1011-1019.doi: 10.3969/j.issn.1000-1093.2017.05.022

• 论文 • 上一篇    下一篇

考虑不确定性的进攻作战抢修任务动态调度

陈伟龙1, 陈春良1, 陈康柱2, 刘彦1   

  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)
  • 收稿日期:2016-10-11 修回日期:2016-10-11 上线日期:2017-07-03
  • 通讯作者: 陈春良(1963—), 男, 教授, 博士生导师 E-mail:chen1963@126.com
  • 作者简介:陈伟龙(1988—), 男, 博士研究生。 E-mail: amose_chen@163.com

Dynamic Scheduling of Battlefield Rush-repair Tasks under Uncertainty in Offensive Operation

CHEN Wei-long1, CHEN Chun-liang1, CHEN Kang-zhu2, LIU Yan1   

  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)
  • Received:2016-10-11 Revised:2016-10-11 Online:2017-07-03

摘要: 针对一体化进攻作战中战损装备众多、抢修时间与抢修力量有限的矛盾,将战场抢修、伴随保障、任务动态调度结合起来,进行了进攻作战抢修任务动态调度研究。提出考虑不确定性的进攻作战抢修任务动态调度的现实军事问题,构建其数学模型,分析核心影响因素。针对问题特点,设计了基于变体遗传算法的模型求解方法,并运用Matlab软件进行了15辆待修装备、3个抢修单元的动态调度示例求解。示例结果表明:通过实施抢修任务动态调度,进攻作战部队能够获得约77 h的二次作战总时间,并大大减少决策时间、降低决策工作量和人为决策风险。

关键词: 兵器科学与技术, 抢修任务, 动态调度, 不确定性, 变体遗传算法

Abstract: The dynamic scheduling of battlefield rush-repair tasks is studied in consideration of many damaged equipment, the limited battlefield rush-repair time and power in the integrated offensive operation, which combines battlefield rush-repair, accompanied logistics and task dynamic scheduling. The dynamic battlefield-rush-repair task scheduling under uncertainty, which is a real military problem, is put forward. A mathematical model is established, and the key influence factors are analyzed. A variant genetic algorithm is designed to solve the problem according to its characteristics. A scheduling example with 15 equipment to be repaired and 3 repair groups is solved by using Matlab. The results of example show that offensive forces can get more combat time to participating in offensive operation again about 77 hours through implementing dynamic scheduling of battlefield rush-repair tasks. And it can greatly reduce decision time, decision workload and subjective decision risk. Key

Key words: ordnancescienceandtechnology, rush-repairtask, dynamicscheduling, uncertainty, variantgeneticalgorithm

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