摘要
为优化动态交通下物流配送成本及服务水平,依据交通流量将运输时间分为不同时段的不同分布,建立了具有时间窗约束与物流成本最小的车辆路径混合整数非线性模型,设计了自然数插值编码的遗传算法对模型进行求解,对不同交通状况下配送方案选择进行了仿真比较。仿真结果显示遗传算法是收敛的,依据交通状况选择相应的配送方案,不仅物流成本降低了2%,而且服务水平也提高了5%。
In order to optimize logistics delivery cost and consumer service level under dynamic traffic, transportation time was assorted into different distributions according to traffic, a mixed integer non-linear model of vehicle routing choice with time window constraints was set up to minimize logistics cost, a genetic algorithm with natural number coding was designed to solve the model, the simulation results of different delivery projects were compared. Comparison result shows that the algorithm is convergent, the logistics cost is reduced by 2%, the service level is improved by 5% to vehicle routing choice according to traffic condition. 3 tabs, 5 figs, 16 refs.
出处
《交通运输工程学报》
EI
CSCD
北大核心
2007年第1期111-115,共5页
Journal of Traffic and Transportation Engineering
基金
国家自然科学基金项目(70433003)
关键词
交通规划
动态交通
车辆路径问题
时间窗
遗传算法
traffic planning dynamic traffic
vehicle routing problem
time window
genetic algorithm
