Development a forward-reverse network optimization model with delay reduction and multistage fuzzy demand satisfaction policy

Abstract

Supply chain management is a process in which a number of organizations work together as a supply chain until the raw materials reach the manufacturer and finally, a valuable product is provided to the end consumer. With the increase in population and the increase in environmental sensitivities, the forward-reverse supply chain has attracted a lot of attention, which pursues goals such as optimization, customer satisfaction, responding to their needs in the shortest time with the lowest cost and high quality. In this paper, a forward- reverse multi-product and multi-period network is designed under the condition of uncertainty in the demand parameter. The purpose of the proposed model is to maximize profit by considering customer satisfaction simultaneously and reducing delay and the fuzzy approach has been used to solve the model under conditions of uncertainty. The proposed model is mixed-integer linear programming and for its validation and applicability, it has been solved by GAMS software, a numerical example using simulated data in deterministic and uncertain state. The results of the analysis of the numerical example show that the show that with increasing uncertainty in the demand parameter, the optimal value of the objective function decreases.

Keywords

• forward-reverse supply chain
• demand satisfaction
• delay reduction
• fuzzy