Mathematical programming and game theory optimization-based tool for supply chain planning in cooperative/competitive environments

M. ZAMARRIPA; A. AGUIRRE; C.A. MÉNDEZ; A. ESPUÑA

CHEMICAL ENGINEERING RESEARCH & DESIGN

INST CHEMICAL ENGINEERS

Lugar: London; Año: 2013 vol. 91 p. 1588 - 1600

0263-8762

A multi-objective Mixed Integer Linear Programming (MILP) model is proposed in this paper, devised to optimize the tactical decisions of several Supply Chains (SC?s) with multiple objectives under uncertain competition behavior. Game Theory optimization has been used as a decision making tool, to deal with cooperative and/or competitive scenarios. Three different optimization criteria are considered (total cost, total delivery time and expenses of the buyers for the competitive problem). The multi objective problem has been solved using the Pareto frontier solutions, and both cooperative and non cooperative scenarios are considered, so multiple optimization tools/techniques (Game Theory, MILP based approach and Pareto frontiers) have been combined to improve the decision making, analyzing the different trade-offs associated to the policies related to planning problems under uncertainty. The model has been probed in a real multi-product, multi-echelon Supply Chain case study, based on the operation of two different SC?s in both competitive and cooperative situations.