Profitability and energy efficiency depend on optimal operation of a supply chain network for automotive fuels in Mexico, even for clean energy expectations. This paper shows how decision‐making for fuels‐distribution network growth in Mexico points in the same direction, while the practical small optimization model, introduced in this paper, replaces a detailed model thereby offering great advantages to the analysts. The paper also describes the relevant strategies that were applied to ensure equivalences between the two models representing a supply chain. The model simplification not only reduces its size and computer time for execution but allows for the most relevant time reduction associated with preparing the data input to feed into the model, as well as in analyzing the results. Some distribution network growth options were evaluated by using both models with equivalent objective functions. Small model results give enough information for decision‐making support. The use of new facilities and economic benefits are similar to those obtained with the complex model. The main issues to take care of are bottleneck identification and commodities differentiation. If a binding constraint is removed in the small model, similar results are seen in the complex model when a specific bottleneck is improved. This is the first time that a practical model is used to evaluate multiple scenarios of the complex automotive fuel distribution network in Mexico.

中文翻译：

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墨西哥汽车燃料供应链增长优化的实用模型

盈利能力和能源效率取决于墨西哥汽车燃料供应链网络的最佳运行，甚至是对清洁能源的期望。本文说明了墨西哥燃料分配网络增长的决策是如何朝着同一方向发展的，而本文介绍的实用的小型优化模型取代了详细的模型，从而为分析师提供了巨大的优势。本文还描述了用于确保代表供应链的两个模型之间的等效性的相关策略。简化模型不仅减少了执行的大小和计算机时间，而且还减少了与准备输入到模型中的数据输入以及分析结果相关的最相关的时间。通过使用两个具有相等目标函数的模型，评估了一些分销网络的增长选择。小模型结果为决策支持提供了足够的信息。新设施的使用和经济利益与复杂模型所获得的相似。要注意的主要问题是瓶颈识别和商品差异化。如果在小型模型中删除了约束条件，则当改善特定瓶颈时，在复杂模型中会看到相似的结果。这是首次将实用模型用于评估墨西哥复杂的汽车燃料分配网络的多种情况。新设施的使用和经济利益与复杂模型所获得的相似。要注意的主要问题是瓶颈识别和商品差异化。如果在小型模型中删除了约束条件，则当改善特定瓶颈时，在复杂模型中会看到相似的结果。这是首次将实用模型用于评估墨西哥复杂的汽车燃料分配网络的多种情况。新设施的使用和经济利益与复杂模型所获得的相似。要注意的主要问题是瓶颈识别和商品差异化。如果在小型模型中删除了约束条件，则当改善特定瓶颈时，在复杂模型中会看到相似的结果。这是首次将实用模型用于评估墨西哥复杂的汽车燃料分配网络的多种情况。