Capacities-based supply chain network design considering demand uncertainty using two-stage stochastic programming

The design of a supply chain (SC) aims to minimize cost so the product can reach the customer at the cheapest cost with flexible demand. The demand of a product is variable with time and environment. Most of the researchers have considered investment cost, processing cost, and transportation cost as variable costs to minimize the cost while considering a constant demand. In actual practice, the demands are flexible. In this paper, a two-stage stochastic programming model has been proposed for a capacities-based network design of a supply chain for flexible demands while considering inventory carrying cost and missed opportunity cost in addition to the above-mentioned costs. It will enhance the logistic planning and seek the location network optimally. Furthermore, in the first stage, decision variables represent different nodes (facility locations of echelons) of the supply chain, with the assumption that they will be considered at the design stage before uncertain parameters are unveiled. On the other hand, decision variables related to the amount of products to be produced and stored in the nodes of the SC, the flows of materials among the entities of the network, and shortfalls and excess at the customer centers are considered as second-stage variables. The methodology has been illustrated by solving an example. It was found that the proposed model yields more feasible and advantageous results.