Coordinating supply chain decisions: an optimization model

Coordinating information and material flows are key to effective supply chain management. The complexity of interactions in and the uncertainties surrounding supply chains make such coordination difficult. However, coordination can be realized by optimizing the flows in supply chains with analytical approaches. A mixed integer programming model is presented to support the tactical decisions of ordering, producing and transporting under various conditions of information availability at the loci of decision making. The model is applied to a modified version of MIT's well known Beer Distribution Game. The performance of the modeling approach is contrasted with the results of human decision making under identical conditions and underlines the enormous potential for performance improvement analytical decision support can provide. Several methodological aspects for coping with the difficulties of solving rather large mixed integer models are presented and it is shown that they can contribute significantly in dealing with the inherent computational problems.