A new multi-criteria scenario-based solution approach for stochastic forward/reverse supply chain network design

Abstract

Analyzing current trends in supply chain management, lead to find unavoidable steps toward closing the loop of supply chain. In order to expect best performance of Closed-Loop Supply Chain (CLSC) network, an integrated approach in considering design and planning decision levels is necessary. Further, real markets usually contain uncertain parameters such as demands and prices of products. Therefore, the next important step is considering uncertain parameters.

In order to cope with designing and planning a closed-loop supply chain, this paper proposes a multi-period, multi-product closed-loop supply chain network with stochastic demand and price in a Mixed Integer Linear Programming (MILP) structure. A multi criteria scenario based solution approach is then developed to find optimal solution through some logical scenarios and three comparing criteria. Mean, Standard Deviation (SD), and Coefficient of Variation (CV), which are the mentioned criteria for finding the optimal solution. Sensitivity analyses are also undertaken to validate efficiency of the solution approach. The computational study reveals the acceptability of proposed solution approach for the stochastic model. Finally, a real case study in an Indian manufacturer is evaluated to ensure applicability of the model and the solution methodology.