基于蒙特卡洛仿真和遗传算法的车辆装备保障运输网络优化

车辆装备保障运输网络优化是影响非战争军事行动任务效果的关键环节。传统方法描述随机且不连续装备保障需求的能力弱，应用于非战争军事行动车辆装备保障运输网络优化方面，会导致结果不稳定。为解决这些问题，提出了基于蒙特卡洛仿真和遗传算法的车辆装备运输网络优化模型。结合非战争军事行动特点，利用边界条件设定，保障资源调度优化函数及保障资源约束条件设置，构建了车辆装备保障运输网络优化模型；采用遗传算法，在路网和运输路径两个层次对车辆装备保障运输网络进行寻优，进一步提高了运算结果的稳定性。通过残差分析验证了该模型的有效性。

Vehicle Equipment Support Transport Net Optimization Model Based on Monte Carlo Simulation and Genetic Algorithm

The vehicle equipment support transport net is the key segment that impacts the mission completion of the military operation other than war. The tranditional method may result in the unstable results in its application in the optimization of vehicle equipment support transport net are obtained because of the poor ability of to describe the random and discontinuous support needs. An optimization model of vehicle equipment transport net is proposed based on Monte Carlo simulation and genetic algorithm. The boundary condition, support resource scheduling optimization function and support resource restraint condition are set according to the support feature of military operation other than war. An optimization model of vehicle equipment transport net is constructed. Finally, the efficiency of the proposed model is verified by residual analysis.