计算机工程与应用2019，Vol.55Issue(12)：1-8,8.DOI:10.3778/j.issn.1002-8331.1804-0023
前摄性车辆路径问题及其遗传算法求解
Improved Genetic Algorithm for Pro-active Dynamic Vehicle Routing Problem
摘要
Abstract
Based on the forecasting and solving algorithm of the uncertain demand in the dynamic vehicle routing prob-lem with uncertain demand information in the existing literature, a multidimensional data layer customer demand forecasting method and a proactive real-time control method are established to discuss the potential customer response criteria. The mathematical model of dynamic vehicle routing problem is established by introducing proactive real-time control method with the aim of minimizing the total transportation cost. The genetic algorithm is used to solve the model. The test results show that the proposed model and algorithm can respond to the customer’s demand more timely and effectively by ap-plying the Joybuy’s distribution data of 20 clients in Chongqing area and the two-stage comprehensive proactive adjust-ment strategy.关键词
动态车辆路径问题/多维数据层结构/前摄性实时控制/需求预测Key words
dynamic vehicle routing problem/ mutli-data layer structure/ pro-active real-time control method/ demand forecast分类
管理科学引用本文复制引用
葛显龙,薛桂琴..前摄性车辆路径问题及其遗传算法求解[J].计算机工程与应用,2019,55(12):1-8,8.基金项目
国家自然科学基金(No.71502021) （No.71502021）
教育部人文社会科学基金(No.2014YJC630038,No.2015XJC630007) （No.2014YJC630038,No.2015XJC630007）
博士后科学基金(No.2016T90862) （No.2016T90862）
重庆市基础与前沿研究(No.cstc2016jcyjA0160). （No.cstc2016jcyjA0160）
