DISTRIBUTION NETWORK OPTIMIZATION: A CASE STUDY FOR A FAST MOVING CONSUMER GOODS COMPANY

The projects presented in this work use real-world data collected from a Fast-Moving Consumer Goods company to model its distribution network. A Facility Location Problem (FLP) was developed to find the optimal location for the warehouse. The optimization problem was solved using the Generalized Reduced Gradient (GRG) method. The results show the current warehouse is very well located and the savings of relocating the operations do not justify the investment. In addition, a feasibility study of adding one warehouse to the network was conducted and the problem was modeled as a multi-commodity p-median problem. The model was solved with both the GRG Method and a Genetic Algorithm. The results confirmed the opportunity of saving up to €45 000 per month by adding a warehouse to the supply network. Finally, it was studied the opportunity of direct shipping from a German factory to the French market and a cross-docking solution to reduce the warehouse handling costs. The study shows the solution delivers up to €120 000 in savings per month in the best scenario making it extremely profitable.