Improving Supply Chain Planning in a Competitive Environment

Article

Authorship

Zamarripa, Miguel A. ; Aguirre, Adrian Marcelo ; MENDEZ, CARLOS ALBERTO ; Espuña, Antonio

Date

2012

Publishing House and Editing Place

Elsevier

Magazine

COMPUTERS AND CHEMICAL ENGINEERING, vol. 42 (pp. 178-188) Elsevier

Summary Information provided by the agent in SIGEVA

This work extends the use of a Mixed Integer Linear Programming (MILP) model, devised to optimize the Supply Chain planning problem, for decision making in cooperative and/or competitive scenarios, by integrating these models with the use of the Game Theory. The system developed is tested in a case study based in previously proposed Supply Chain, adapted to consider the operation of two different Supply Chains (multi-product production plants, storage centers, and distribution to the final cons... This work extends the use of a Mixed Integer Linear Programming (MILP) model, devised to optimize the Supply Chain planning problem, for decision making in cooperative and/or competitive scenarios, by integrating these models with the use of the Game Theory. The system developed is tested in a case study based in previously proposed Supply Chain, adapted to consider the operation of two different Supply Chains (multi-product production plants, storage centers, and distribution to the final consumers); two different optimization criteria are used to model both the Supply Chains benefits and the customer preferences, so both cooperative and non-cooperative way of working between both Supply Chains can be considered.