An Effective Heuristic Algorithm for Robust Supply Chain Network Design under Uncertainty

Abstract

This paper addressing a study on robust supply chain network design under uncertainty environment. We use decomposition and coordination strategy to decompose the model as two parties: the first part is facility location decision which only concludes 0 − 1 decision variable, tabu search algorithm is used to determine the 0 − 1 decision variables, and then regard the 0 − 1 variables as known input parameters. The second part is flow decision, all-or-nothing method is proposed to design the capacity of the facility. From the numerical example, we can see that, the model and algorithm is valid and effective, the robust optimization model not only reduces the risk of market, but avoids the error from the shortage cost.

A Robust Optimization Approach to Supply Chain Cost Optimization

“…Delage and Ye (2010) and Wiesemann et al (2014) investigated the idea of Distributionally Robust Optimization to examine models with uncertain parameters. Aghezzaf (2005) and Jin et al (2014) tested model robustness measures for Supply Chain Network Design (SCND).…”