A new robust possibilistic programming model for reliable supply chain network design: A case study of lead-acid battery supply chain

Abstract

Nowadays, the importance of caring about tremendous undesirable economical and technological effects of disruptions has impelled many researchers to design reliable supply chain networks. Moreover, the issue of intrinsic imprecision of input parameters should be gingerly regarded in the design of supply chain networks because it could have inverse impact on the quality of long-term planning decisions. Consequently, to handle the noted problems, in this paper, a reliable closed-loop supply chain network is formulated in which a new reliability method is introduced. The proposed formulation can effectively enable the design of a reliable network under different kinds of disruptions besides seeking for minimum overall costs of network design. On the one hand, a new effectual robust possibilistic programming (RPP) model is developed to confront with business-as-usual uncertainty in input parameters. Lastly, a real industrial case study is employed to validate the utility and practicability of the rendered model as well as presenting the efficiency and felicity of the developed RPP model.