摘要
为提高军事后勤车辆的配送效率,实现快速响应,文中在分析军事后勤车辆路径问题特点的基础上,建立了单时间窗多目标动态军事后勤车辆路径模型,设计了遗传-蚁群混合算法对模型进行两阶段求解.仿真实验结果表明,该算法解决了遗传算法求解效率低及蚁群算法收敛过早的问题,可有效解决军事后勤车辆动态路径优化问题.
In order to improve the distribution efficiency of military logistics vehicles and realize the quick response, a multi-objective dynamic military logistics vehicle routing model with a single time window was established based on the analysis of the characteristics of military logistics vehicle routing.And then a Genetic Ant Colony Hybrid Algorithm of two stages was designed for the model. The simulation results show that the hybrid algorithm overcomes the lower efficiency of the genetic algorithm and the premature convergence of the Ant colony algorithm. It can effectively optimize the dynamic routing of the military logistics distribution vehicles.
出处
《西安工业大学学报》
CAS
2015年第1期63-69,共7页
Journal of Xi’an Technological University
基金
陕西省社会科学基金(12D156)
关键词
配送
时间窗
动态
车辆路径问题
遗传蚁群混合算法
distribution
time window
dynamic
vehicle routing problem （VRP）
genetic ant colony hybrid algorithm
