基于模糊聚类分析的车辆优化调度  

Optimal vehicle routing problem based on fuzzy clustering analysis

作　　者：鹿应荣[1] 杨印生[1] 吕锋[2] 

机构地区：[1]吉林大学生物与农业工程学院,长春130022 [2]河南科技大学机电工程学院,洛阳471003

出　　处：《吉林大学学报（工学版）》2006年第S2期147-151,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林省科技发展规划项目(20040528)

摘　　要：应用模糊聚类分析对物流配送需求点进行分类,建立了车辆调度问题的数学模型,将标准遗传算法与爬山算法集成,构造了一种改进的混合遗传算法。试算结果表明,对需求点分类后,应用遗传算法可有效解决联合物流模式的车辆调度问题。The demand points for physical distribution were classified by the fuzzy clustering analysis,and a mathematical model for the vehicle routing problem was established.An improved hybrid genetic algorithm integrating the standard genetic algorithm and the climb-up algorithm was constructed.The trial calculation results show that vehicle routing problem for logistics alliance model can be solved efficiently by the improved hybrid algorithm through the classification of the demand points.

关 键 词：交通运输工程 车辆调度 遗传算法 模糊聚类 

分 类 号：U116.1[交通运输工程]