基于量子遗传算法的作战油料调运优化  

Research on POL Distribution Transportation Optimization Based on Quantum Genetic Algorithm

作　　者：王帅 郭月凯 屈少辉 朱愈欢 王灿 陈宇昕 WANG Shuai;GUO Yuekai;QU Shaohui;ZHU Yuhuan;WANG Can;CHEN Yuxin(Army Logistics College of PLA,Chongqing 401331;No.32322 Troops of PLA,Urumqi 830000)

机构地区：[1]中国人民解放军陆军勤务学院,重庆401331 [2]中国人民解放军32322部队,乌鲁木齐830000

出　　处：《舰船电子工程》2021年第10期121-125,共5页Ship Electronic Engineering

基　　金：军队军事后勤科研计划项目“军事能源发展战略研究”(编号:CX217L007)资助。

摘　　要：针对油料保障优化问题,引入多时间窗口,考虑了油料保障的复杂时间约束和运力约束,提出了基于多时间窗口的调度模型。在求解算法上,运用量子遗传算法对油料供给点、需求点、时间窗约束和油料储量运量约束等条件进行量子比特编码,构建了最大限度地满足需求点的需求,同时保证各需求点开始保障的时间尽可能早的适应性函数,并通过量子旋转门等操作使量子编码染色体进行进化,得到优化后的油料调度方案。最后,对模型和算法进行了仿真实验,实验表明,量子遗传算法解决复杂时间窗约束条件下的油料调度问题具有全局搜索性强,收敛性较好的优点,并通过调度方案的可视化为科学决策提供了依据。For the optimization problem of oil security,multiple time windows are introduced,the complex time constraints and capacity constraints of oil security are considered,and a scheduling model based on multiple time windows is proposed.In the solution algorithm,quantum genetic algorithm is used to quantum bit encode the conditions of oil supply point,demand point,time window constraint and oil storage capacity constraint,and constructs an adaptive function that maximizes the demand point's demand while ensuring that each demand point starts securing as early as possible.It evolves the quantum encoded chromosome through operations such as quantum revolving gate to obtain the optimized oil scheduling scheme.Finally,the simulation experiments of the model and algorithm are conducted,which show that the quantum genetic algorithm has the advantages of strong global search and good convergence in solving the fuel scheduling problem under complex time window constraints.It provides a basis for scientific decision-making through the visualization of the scheduling scheme.

关 键 词：战时油料保障 约束满足问题 优化模型 量子遗传算法 多时间窗口 

分 类 号：E239.1[军事—军事理论]