摘要
以配送费用最小为目标,在考虑客户服务优先级、车辆装载率、危险物资不能混装等约束条件下,构建了单车场多仓库多趟配送车辆路径问题模型,并用改进的遗传算法进行求解,将郑州煤电物资供销有限公司的物资配送作为案例进行研究,从配送费用、配送里程、使用车辆数、车辆装载率、车辆最晚返回时间和保证服务优先级等指标评价改进的遗传算法的优化性能,结果表明了算法的有效性。
Aiming at minimizing the distribution cost, considering the constraints on the service priority of consumers, the load rate of vehicles and the immiscible packing of dangerous materials, we build a multi- trip distribution model of single-depot and multi-warehouse. An improved genetic algorithm is designed to solve the model. Then, using the distribution of dangerous materials for Zhengzhou Coal Mine and Power Supply Co., Ltd. as an example, we evaluate the proposed algorithm based on indices including the distribution cost, the traveling distance, the number of used vehicle, the load rate of the vehicles, the return time of the vehicles and the guarantee of service priority. The results show the efficiency and effectiveness of the proposed algorithm.
出处
《系统管理学报》
CSSCI
2013年第5期728-736,共9页
Journal of Systems & Management
基金
国家自然科学基金资助项目(71173202
71103163)
教育部人文社会科学研究青年基金资助项目(10YJC790071)
中央高校基本科研业务费专项资金资助项目(CUG110411
G2012002A
CUG120111)
关键词
车辆路径问题
煤矿危险物资配送
服务优先级
遗传算法
vehicle routing problem
coal mine dangerous material distribution
service priority
geneticalgorithm
