Modeling Supply Chain Network Design Problem with Joint Service Level Constraint

Abstract

This paper studies a supply chain network design problem with stochastic parameters. A Value-at-Risk (VaR) based stochastic supply chain network design (VaR-SSCND) problem is built, in which both the transportation costs and customer demand are assumed to be random variables. The objective of the problem is to minimize the allowable invested capital. For general discrete distributions, the proposed problem is equivalent to a deterministic mixed-integer programming problem. So, we can employ conventional optimization algorithms such as branch-and-bound method to solve the deterministic programming problem. Finally, one numerical example is presented to demonstrate the validity of the proposed model and the effectiveness of the solution method.