Application of mixed integer programming to a large-scale logistics problem

Time-based competition has a direct impact on logistics operations. Today, logistics costs are increasing rapidly, and tools must be developed to improve logistics operations and reduce its associated costs. This paper describes the development, the application and the successful implementation of a mixed integer programming model for a real-life logistics problem at NedCar, a car manufacturer in the Netherlands. The model determines the ordering dates and quantities of purchase parts given constraints on demand, transportation, packaging and inventory levels, in order to minimize logistics costs. Special consideration is given to reducing the model complexity.