A Robust Reliable Closed Loop Supply Chain Network Design under Uncertainty: A Case Study in Equipment Training Centers

The aim of this paper is to propose a robust reliable bi-objective supply chain network design (SCND) model that is capable of controlling different kinds of uncertainties, concurrently. In this regard, stochastic bi-level scenario based programming approach which is used to model various scenarios related to strike of disruptions. The well-known method helps to overcome adverse effects of disruptions and extend a network that is less vulnerable regarding disruptions strike. Also, scenario-based modeling approach enables decision makers (DMs) to the model uncertainty of model parameters regarding different scenarios that are disregarded in reliable SCND research scope. An effective robust programming method is employed to control the risk-aversion level of output decisions that helps company managers to adjust long-term effects of their decisions via determining uncertainty level of model parameters. Notably, extended bi-objective programming model minimizes total costs of network design aside with maximization of responsiveness of supply chain network. Agile and fast performing networks could be regarded as a long-term competitive advantage for companies that are modeled in the extended form as a different objective besides cost minimization. Finally, the extended robust reliable network model is implemented and evaluated based on real case study of a national project and output results demonstrates efficiency and applicability of proposed reliable network.

Keywords:

Closed loop supply chain , responsiveness , robust optimization , P , robust , Uncertainty , training center