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Hybrid robust, stochastic and possibilistic programming for closed-loop supply chain network design

机译：闭环供应链网络设计的混合鲁棒，随机和可能性编程

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摘要

The main goal of this study is to address gap in the area of Closed-loop Supply Chain Network Design (CLSCND) under the hybrid uncertain conditions. To do this, a multi-product and multi-period model is developed in an edible oil supply chain. Since the proposed model includes two kinds of uncertain parameters, the scenario- and fuzzy-based parameters, a novel Robust Stochastic-Possibilistic Programming (RSPP) are proposed to cope with uncertain parameters, based on the Me measure. Furthermore, the performance of the RSPP model is reviewed, its weaknesses and strengths are studied, and it is compared with the other models. Finally, the usefulness and applicability of the RSPP model are tested by the real industrial case study.
机译：这项研究的主要目标是解决混合不确定条件下闭环供应链网络设计（CLSCND）领域的空白。为此，在食用油供应链中开发了多产品，多时期的模型。由于所提出的模型包括基于场景和模糊的两种不确定性参数，因此基于Me度量，提出了一种新颖的鲁棒随机可能规划（RSPP）来应对不确定性参数。此外，回顾了RSPP模型的性能，研究了它的弱点和优点，并将其与其他模型进行了比较。最后，通过实际的工业案例研究测试了RSPP模型的有用性和适用性。

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