Data envelopment analysis approaches for two-level production and distribution planning problems
Data envelopment analysis approaches for two-level production and distribution planning problems
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DOI：
10.1016/j.ejor.2021.07.047
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
I. Nishizaki;Tomohiro Hayashida;Shinya Sekizaki;Junya Okabe
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文献类型：
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作者：
I. Nishizaki;Tomohiro Hayashida;Shinya Sekizaki;Junya Okabe
在本文中，我们专注于两个层次的生产和分销计划问题的供应链管理领域，并检查的情况下，领导者不完全知道的制造技术的追随者。在这种情况下，代表制造技术的参数不能明确地用于制定追随者的生产计划问题。为了克服这一困难，我们提出的配方，隐式地表达制造技术，通过使用从生产活动的追随者观察到的投入产出数据，结合数据包络分析（DEA）的想法。假设跟随者有多个生产设施，我们考虑了两种可能的可观察的投入产出数据，并制定相应的两个生产计划问题：第一，只有投入产出数据聚合的所有生产设施可以被观察到集体，第二，投入产出数据为每个生产设施可以单独观察。为了澄清这些DEA方法的有效性，我们比较了它们与传统的配方技术系数使用数值例子。
In this paper, we focus on a two-level production and distribution planning problem in the field of supply chain management, and examine the situations where the leader does not fully know the manufacturing technologies of the follower. In such a situation, the parameters representing the manufacturing technologies cannot be explicitly used to formulate the follower’s production planning problem. To overcome this difficulty, we propose formulations that implicitly express manufacturing technologies by using the input-output data observed from the production activities of the follower, incorporating the idea of data envelopment analysis (DEA). Assuming that the follower has multiple production facilities, we consider two possibilities of the observable input-output data and formulate two corresponding production planning problems; firstly, that only the input-output data aggregated for all the production facilities can be observed collectively, and secondly, that the input-output data for each of the production facilities can be observed separately. To clarify the validity of these DEA approaches, we compare them with the conventional formulation with technological coefficients using a numerical example.