基于客户动态需求属性的物流配送线路聚类优化

Distribution Routes Clustering and Optimization based on Customer Dynamical Demand Attributes

随着经济发展和技术进步,物流配送面临日益复杂和多变的客户需求并成为电子商务应用的重要制约因素和瓶颈环节。根据客户需求特点,提出了一种反映客户动态需求属性的物流配送线路聚类优化方法。提出了一种可以反映多种客户需求属性的模糊系统聚类方法进行客户分类,运用智能加权对动态属性进行集成和生成相应的配送策略。本文的客户动态需求属性不同于大多数车辆路径问题(VRP)文献所考虑的静态地理属性。理论分析结果表明,常见的"按时间配送"和"按范围配送"成为本文新方法在不同属性权重下的2个特例。最后,通过一个单、双向混合配送线路选择算例表明新方法的有效性和实用性。

With the development of economy and technology,the logistics distribution faces more complicated and dynamical customer requirements,and often becomes the important constraint factor and bottleneck of electrical commerce applications. Based on the characteristics of customer dynamical requirements,we propose an approach for optimizing logistics distribution routes.Firstly,we present a hybrid fuzzy-hierarchical clustering of multi-attribute of customer requirements for customer classifications.Then,the intelligent weighted aggregation is applied for the attributes,and the distribution strategies are generated.The dynamical customer requirements are different from the statistical geographical attributes in most Vehicle Routing Problem（VRP）.The theoretical analysis shows that,the traditional distribution strategies of＂distributing with times＂and＂distributing with locations＂become the special cases of the new approach under different weights values. A hybrid distribution route choice example illustrates the effectiveness and usefulness of the approach.