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Optimization of Cold Chain Distribution Route with Mixed Time Window considering Customer Priority

机译:考虑客户优先的混合时间窗冷链配送路线优化

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摘要

In order to study the mixed time window vehicle routing optimization problem based on customer priority, a customer differentiation management strategy based on customer priority is proposed. Combined with the main factors affecting customer priority evaluation and the characteristics of vehicle routing problem with mixed time windows, a comprehensive evaluation index affecting customer priority was first established and DBSCAN clustering algorithm was used for clustering analysis of customer priority to solve the optimization problem of cold chain distribution route considering customer priority. Fuzzy time window of refrigerated vehicles was then constructed with trapezoidal fuzzy number, and a mathematical programming model was built with an objective function for minimizing the sum of fixed, green, penalty, refrigeration, and cargo damage costs. Two scenarios of out-of-stock and not-out-of-stock were designed. Finally, an improved genetic algorithm was used to solve the model, and the rationality of the model was verified through a case of imported fruit distribution in Xiamen City. Results showed that the proposed method can effectively solve the routing problem of refrigerated trucks considering customer priority. Moreover, the findings of this study can provide a new approach for solving the routing optimization problem of refrigerated trucks considering customer priority.
机译:为了研究基于客户优先级的混合时间窗车辆路径优化问题,提出了一种基于客户优先级的客户差异化管理策略。结合影响客户优先级评价的主要因素和混合时间窗的车辆路径问题特点,首先建立影响客户优先级的综合评价指标,并采用DBSCAN聚类算法对客户优先级进行聚类分析,求解考虑客户优先级的冷链配送路线优化问题。然后,利用梯形模糊数构建冷藏车模糊时间窗,并建立具有最小化固定成本、果岭成本、罚款成本、制冷成本和货物损坏成本之和的目标函数的数学规划模型。设计了缺货和不缺货两种场景。最后,采用改进遗传算法对模型进行求解,并通过厦门市进口水果流通案例验证了模型的合理性。结果表明,所提方法能够有效解决考虑客户优先的冷藏车路线问题。此外,本研究结果可为解决考虑客户优先的冷藏车路线优化问题提供新的思路。

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