【摘要】 为了研究基于客户重要度的混合时间窗车辆路径优化问题,提出了基于顾客价值理论的客户差异化管理策略。结合影响客户重要度评价的主要因素和混合时间窗车辆路径问题的特性,建立了影响客户重要度的综合评价体系,提出用三角模糊数表示语言变量值,并对客户点进行综合评价。采用了模糊集成方法将客户评价指标进行集成计算,将集成后的方案评价指标值作为模糊k-means聚类算法的输入进行聚类操作,设计了聚类有效性指标选取合理聚类方案。分析了基于聚类结果的客户重要度划分方案,提出了基于客户重要度和客户服务时间窗相结合的差异化管理策略,构建了基于配送成本、车辆维护成本、违反时间窗惩罚成本之和最小化和配送车辆数最小化的双层数学规划模型,设计了一种GA-TS混合智能算法求解模型。通过实例对构建的模型和设计的算法进行了合理性验证,并进行了不同算法计算结果比较和敏感度分析研究。结果表明:该方法能有效解决基于客户重要度的混合时间窗车辆路径问题,且评价指标体系中商品需求规模和客户发展潜力值两个指标的敏感性较高。本研究为解决基于客户重要度的车辆路径优化相关问题提供了新的思路。更多还原

【Abstract】 In order to study the vehicle routing problem with mixed time windows based on importance of customers, the difference management strategy for customers based on customer value theory is proposed. Combining the main factors influencing the evaluation of customer importance and the characteristics of vehicle routing problem with mixed time windows, a comprehensive evaluation system of influencing the importance of customers is established, the linguistic variables are represented by triangular fuzzy number to implement the comprehensive evaluation of customer points. Then, the customer evaluation indicators are integrated by fuzzy integration, and the integrated evaluation index values are used as the input of fuzzy k-means clustering algorithm for clustering, with a clustering validity indicators being designed to choose the reasonable clustering scheme. Moreover, the customer importance partition scheme based on clustering result is analyzed, and the difference management strategy for customers based on customer importance and customer service time windows is proposed, a bi-level mathematical programming model based on minimum sum of distribution cost, vehicle maintenance cost and penalty cost for violation of time windows as well as minimum number of distribution vehicles is established, and a GA-TS hybrid intelligent algorithm is devised to solve the model. The rationality of the proposed model and the algorithm is verified through an example, and the comparison of the calculation results of different algorithms and the sensitivity analysis are carried out. The result shows that the vehicle routing problem with mixed time windows based on the importance of customers can be effectively solved by the proposed method, and the sensitivity of 2 indexes including commodity demand scale and potential value of customer development is higher in the evaluation index system. The study provides a new idea for solving the vehicle routing optimization problem based on the importance of customers.更多还原