A Robust Fuzzy-Probabilistic Programming Model for a Reliable Supply Chain Network Design Problem

Supply chain network design decisions are among the strategic decisions of supply chain management which play significant role on the efficient performance of the supply chain. However, there are two challenging factors which may have great impact on the supply chain performance. These factors are on the one hand disruptions and their attendant damages and on the other hand uncertain nature of business-as-usual parameters. Therefore, the supply chain being designed should be reliable against disruptions as well as should be robust under business-as-usual uncertainty. This paper proposes a new robust fuzzy-probabilistic programming model for designing a reliable multi-period supply chain network which can cope with the two challenging factors, simultaneously. At first, in order to design a reliable model, by taking into account two types of facilities, that are fail able and non-fail able against probabilistic disruptions, a hard worst case approach is employed. Then to deal with business-as-usual uncertainty a robust fuzzy programming is developed. Flexible constraints of customers and determining the optimum level of satisfying these constraints is also considered in the model. Furthermore, to incorporate the concept of reliability in the problem and to cover the important features of real life supply chains, uncertain partial disruption and constraints of expected delivery time of customers are taken into account in the model. Finally, an industrial case study related to a manufacturer engaged in the healthcare system of Iran is applied to demonstrate the effectiveness and the applicability of the developed model.