A stochastic bi-objective multi-product programming model to supply chain network design under disruption risks

Emphasize on cost-cutting, increasing customers' satisfaction, and trying to manage and reduce the risks are among the key strategies of decision-makers in the design of supply chain networks. This study provides a stochastic bi-objective multi-product optimization model for designing a resilient supply chain network under disruption risks. The objectives of the proposed model are minimizing the total cost of the supply chain, as well as, minimizing the non-resiliency of the network. In addition, a ε-constraint method is used to convert the bi-objective model into a single-objective formulation. The model decisions include locating manufacturers, warehouses, and distribution centers and determining the amount of production of different products in each manufacturer, the amount of product transport between the different nodes of the network, and the amount of lost sales for different products in each market. The validity of the proposed model is investigated through random examples and the results of the model implementation on these examples are presented.