摘要
针对现代网络销售过程中配送路线规划的实际问题,充分考虑客户收货点的随机性、分布散的特点,将配送区域划分为合理的投递网点,转化为对投递点的路径优化问题,以最小化行驶里程目标,建立了物流配送路径优化模型,提出基于聚类的改进两阶段启发式算法。通过第一阶段的聚类算法,对配送网点进行划分,大幅降低问题规模,将问题转化为小规模的单车线路优化问题;第二阶段对每个分区内的投递网点,采用遗传算法求解。实验结果表明该算法能够整体上大幅降低企业配送成本。
Due to practical problems on vehicle routing problem of regional E-retailer, dispersion of customer receipt points,distribution area are divided into reasonable considering the randomness and deliver point. The problem is transformed into the deliver point of distribution routing problem. This paper,proceeding from distribution routes division and reducing distribution cost,establishes the optimizing model,which has the objective of minimum distribution distance,and introduces an improved two-phase algorithm based on clustering. Namely,the distribution region can be divided into several parts in the first phase, which can greatly reduce the scale of the problem and traosform the problem into the traveling salesman problem;in the second phase,we get the solutions of the customer points in every group using the genetic algorithm. In the end, the test proves that the algorithm, with practical value and broad application prospect, can greatly reduce the distribution cost.
出处
《科技与管理》
2011年第2期82-85,共4页
Science-Technology and Management
关键词
车辆路径
配送物流
聚类
遗传算法
网络零售商
vehicle routing
logistic system
clustering
genetic algorithm
E-retailer