• 论文 •    

多车型动态需求车辆路径问题建模及优化

张景玲,赵燕伟,王海燕,介婧,王万良   

  1. 1.浙江工业大学 特种装备制造与先进加工技术教育部重点实验室,浙江杭州310012;2.浙江工业大学 计算机科学与技术学院,浙江杭州310012
  • 出版日期:2010-03-15 发布日期:2010-03-25

Modeling and algorithms for a dynamic multi-vehicle routing problem withCustomers'dynamic requests

ZHANG Jing-ling, ZHAO Yan-wei, WANG Hai-yan, JIE Jing, WANG Wan-liang   

  1. 1.Key Laboratory of Special Equipment & Advanced Processing Technology Ministry of Education,Zhejiang University of Technology, Hangzhou 310012,China;2.College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310012, China
  • Online:2010-03-15 Published:2010-03-25

摘要: 针对现代物流配送系统中客户需求动态变化、配送中心车型多样化以及车辆行驶路线开放式的特点,建立了多车型开放式动态需求车辆路径问题的两阶段数学规划模型。制定了相应的“预优化路线调度”和“实时动态调度”的两阶段求解策略,提出了混合2-OPT量子进化算法的求解方法,设计了一种将常用的整数编码转换为量子比特的编码方法,每一个染色体都代表一种行车路线方案,对于量子进化算法求得的行车路线方案,引入2-OPT优化方法,对线路内的子路径进行局部调整,进一步提高了算法的收敛速度。最后通过实例测试及与其他算法的比较,验证了该方法的有效性。

关键词: 物流, 车辆路径, 动态需求, 多车型, 两阶段模型, 混合量子进化算法

Abstract: Aiming at the dynamic changes of customer requirements, vehicles'diversification and open routes in the dynamic vehicle routing problem (DVRP), a two-phase mathematic programming model was presented for the dynamic vehicle routing problem. Corresponding two-phase solutions of “Pre-optimization Route Scheduling” and “Real-time Dynamic Scheduling” were established. And a Hybrid 2-OPT Quantum-Inspired Evolutionary Algorithm (HQEA) for this dynamic problem was proposed. In the HQEA, an encoding method of converting Q-bit representation to integer representation was designed. Every chromosome represented a kind of route. The 2-OPT algorithm was introduced to optimize sub-routes for convergence acceleration. Finally, some examples were tested and were compared with other algorithms.The effectivness of this method was verified by case study and comparing with the other methods.

Key words: logistics, vehicle routing, dynamic requests, multi-vehicle, two-phase mathematic model, hybrid quantum evolutionary algorithm

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