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A Two-Phase Heuristic Algorithm for the Common Frequency Routing Problem with Vehicle Type Choice in the Milk Run

机译：牛奶运行中带车辆类型选择的共频路由问题的两阶段启发式算法

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摘要

High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT) strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, frequency planning, and vehicle type choice in order to optimize the sum of the cost of transportation, inventory, and dispatch. To this end, we develop a mathematicalmodel to describe the common frequency problem with vehicle type choice. Since the problem is NP hard, we develop a two-phase heuristic algorithm to solve the model. More specifically, an initial satisfactory solution is first generated through a greedy heuristic algorithm to maximize the ratio of the superior arc frequency to the inferior arc frequency. Following this, a tabu search (TS) with limited search scope is used to improve the initial satisfactory solution. Numerical examples with different sizes establish the efficacy of our model and our proposed algorithm.
机译：高频率和小批量是牛奶运行的特征，通常用于在物流系统中实施实时（JIT）策略。共同的频率问题，同时涉及到路线和频率的规划，已经在牛奶运行系统中得到了广泛的研究。此外，牛奶运行系统中车辆类型的选择也对运营成本产生重大影响。因此，在本文中，我们同时考虑了车辆路线规划，频率规划和车辆类型选择，以优化运输，库存和调度成本的总和。为此，我们开发了一个数学模型来描述车辆类型选择中的常见频率问题。由于问题很难解决，因此我们开发了一种两阶段启发式算法来求解模型。更具体地，首先通过贪婪启发式算法来产生初始令人满意的解决方案，以最大化上电弧频率与下电弧频率的比率。此后，使用搜索范围受限的禁忌搜索（TS）来改善初始令人满意的解决方案。不同大小的数值示例建立了我们的模型和提出的算法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第20期|404868.1-404868.13|共13页
  • 作者

    Lin Yu; Xu Tianyi; Bian Zheyong;

  • 作者单位

    Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China;

    Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China;

    Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China;

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