基于变体GA的进攻作战抢修任务动态调度  

Dynamic scheduling of battlefield rush-repair tasks in the offensive operation based on variant GA

作　　者：陈伟龙[1] 陈春良[1] 史宪铭[2] 高恒 CHEN Weilong CHEN Chunliang SHI Xianming GAO Heng(Department of Technique Support, Academy of Armored Force Engineering, Beijing 100072, China Department of Equipment Command and Management, Ordinance Engineering College, Shijiazhuang 050003, China Department of Self-propelled Gun, Nanjing Artillery Academy, Nanjing 211132, China)

机构地区：[1]装甲兵工程学院技术保障工程系,北京100072 [2]军械工程学院装备指挥与管理系,河北石家庄050003 [3]南京炮兵学院自行火炮系,江苏南京211132

出　　处：《系统工程与电子技术》2017年第3期577-583,共7页Systems Engineering and Electronics

基　　金：军队保障科研项目资助课题

摘　　要：针对进攻作战中装备不断损伤,而抢修时间与抢修力量有限的突出矛盾,提出了"如何动态地为各抢修组优选最佳待修装备、明确不同抢修组间的任务分工和同一抢修组内的抢修序列,使得损伤装备获得尽可能多的二次作战时间"的现实军事问题。抽象出进攻作战抢修任务动态调度这一新问题,构建了其数学模型,设计了变体遗传算法进行编程求解。运用Matlab软件进行了28待修装备3抢修组的调度实例求解,实例证明提出的模型科学合理,求解算法方便高效,能够动态地追踪问题最优解的变化。In the offensive operation, equipment is constantly being damaged, but the battlefield rushrepair time and power are limited. Therefore, a real military problem is put forward as follows. In order to get more fighting time for damaged vehicles to participate in operation again as much as possible, the problem is how to dynamically choose the most suitable damaged equipment for each repair group, how to divide tasks between different groups, and how to determine execution sequence in the same group. Then the dynamic battlefield-rush-repair-task scheduling problem in the offensive combat is abstracted as a new problem. Its mathematical model is established and a variant genetic algorithm is designed to solve it. A scheduling example is solved by using Matlab with 28 equipment to be repaired and 3 repair groups. Results show that the proposed model is scientific and reasonable, and the algorithm is convenient and efficient, which can dynamically track the change of the optimal solution.

关 键 词：进攻作战 抢修任务 动态调度 变体遗传算法 

分 类 号：E92[军事—军事装备学]