战时车辆调度问题算法及应用分析

An Algorithm and Its Application on Vehicle Scheduling Problem in Wartime

战时车辆调度是精确后勤的核心内容之一,对提高部队机动性和后勤保障能力具有重要作用。对战时车辆调度问题进行分析研究,提出一种快速、高效的算法。对战时多任务车辆调度组合优化问题,即NP-Hard问题进行求解。构造了一个两层搜索结构的遗传禁忌混合算法,该算法充分利用了不同领域搜索方法的优点,增强了算法在解空间中的搜索能力和运行效率。试验分析结果表明:所提算法能有效地解决战时多任务车辆调度问题;与基本遗传算法相比,该算法的优化能力、运行效率、可靠性均得到了提高。

Optimization of vehicle scheduling problem in wartime is a core content of exact logistics.It plays an important role in enhancing motility and logistics capability for army.The vehicle scheduling problem in wartime is studied and analyzed,and a fast and high-efficient algorithm is proposed to solve the multi-task vehicle scheduling problem,which is a combinatorial optimization problem,namely,a NP-Hard issue.A hybrid genetic-tabu meta-heuristic algorithm which has a double-layer searching structure is constructed.The advantages of different optimization methods and strengthens algorithm search ability and operational efficiency are combined.Experimental results demonstrate that the proposed algorithm has the capability to effectively solve the multi-task vehicle scheduling problem in wartime.Compared with basic genetic algorithms,the capability of optimization,efficiency of operation and reliability are all improved.