A metaheuristic approach for supply chain network design problems

Abstract

We develop a multi-objective stochastic programming model for supply chain design under uncertainty using a metaheuristic approach. This is a comprehensive model, which includes both the strategic and tactical levels. The uncertainty regarding demands, supplies, processing and transportation costs is captured by generating discrete scenarios with given probabilities of occurrence. To solve the problem, we use multi-objective simulated annealing and compare the results against the goal attainment technique. Numerical results show that the proposed metaheuristic approach is a very practical solution technique. © 2012 Springer-Verlag.