Abstract

The production planning among many sites is one of the key supply chain management issues. In this research, two decision support models for multi-plant production planning based on mixed-integer linear programming techniques are developed. The first one is a "monolithic model" that considers both the capacity and material constraints and provides an optimal production plan to minimize the overall production cost. The second one is a "two-stage model," which first allocates the customers' orders to different plants under the capacity constraint and the minimum cost objective. With the orders being determined, then in the second stage a different model is used to provide the optimal production plans for individual plants under the material and capacity constraints. Results of simulation study show that the two-stage decision support model is superior and provides the near optimal solutions and requires a very efficient computation effort.