Multi-Plant Production and Transportation Planning Based on Data Envelopment Analysis

Abstract

This paper proposes a methodology for developing a coordinated aggregate production plan for manufacturers producing multiple products at multiple plants simultaneously, in a centralized environment via data envelopment analysis (DEA).
Based on demand forecast of the planning horizon, the central decision maker (DM) specifies the optimal combination of input resources required by the optimal output targets for each plant to keep the supply and demand in balance, and the accompanying transportation trips and volumes among distribution centers (DCs) or warehouse facilities. In this paper, we focus on an integrated production-transportation problem since production and transportation are two fundamental ingredients in the whole operation chain. We deal with multiple products manufactured in multiple plants.
The proposed mixed integer DEA models minimize both production costs and transportation costs. The capacity constraint for each plant is enforced by using the production possibility set theory. Finally, we validate our models by a numerical example and sensitivity analysis.