Fuzzy Programming Approach for Collaborative Supply Chain under Uncertain Demand

Khouloud Dorgham, I. Nouaouri, J. Nicolas, G. Goncalves
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Abstract

Nowadays, improving the performance of the hospital supply chain became increasingly important. Therefore, healthcare organizations strive to optimize operational efficiency and reduce costs. In this paper, we propose a linear programming model to optimize the allocation of material resources (products) to the healthcare establishments within a “Territorial Hospital Group (THG)”. This cooperation among hospitals presents a new form of horizontal collaboration in order to ensure the pooling of stores/pharmacies and minimize logistics costs. Besides, in real-world applications, parameters such as demands and costs could be quite imprecise or uncertain. Moreover, we address in our work uncertainty related to the demands of care units/hospitals due to unusual or unforeseen conditions. This uncertain parameter is modeled as a triangular fuzzy number and we propose a fuzzy linear programming model to solve using the weighted average method for the defuzzification stage. The efficiency of the proposed model is tested over a set of generated instances. The obtained results prove the importance of horizontal collaboration and uncertainty handling.
需求不确定下协同供应链的模糊规划方法
如今,提高医院供应链的绩效变得越来越重要。因此,医疗保健组织努力优化运营效率并降低成本。在本文中,我们提出了一个线性规划模型来优化“区域医院集团(THG)”内医疗机构的物质资源(产品)分配。医院之间的这种合作提供了一种新的横向合作形式,以确保商店/药房的集中并最大限度地降低物流成本。此外,在实际应用中,需求和成本等参数可能相当不精确或不确定。此外,我们在工作中解决了由于不寻常或不可预见的情况而导致的护理单位/医院需求的不确定性。将该不确定参数建模为一个三角模糊数,并提出了一个模糊线性规划模型,在去模糊化阶段采用加权平均法求解。在一组生成的实例上测试了所提出模型的效率。所得结果证明了横向协作和不确定性处理的重要性。
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