Distribution Network Optimization: A case study for a Fast Moving Consumer Goods Company
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Tipus de documentProjecte Final de Màster Oficial
Data2022-02-09
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Abstract
As a company grows over time serving more and more consumers, it needs to invest on its supply chain to be able to keep up with demand and the increased expectations. The same strategic choices that once made the fortune of a company can become quickly outdated when conditions change. In the last decade, it has become even more important for Fast-Moving Consumer Goods companies to be close to their customers, increase the service level and reduce the Supply Chain costs. Within its continuous improvement strategy, Company X required to identify and validate cost reduction strategies for the Distribution Network without reducing the service level. This research aims at confirming if the current supply network of Company X in France is efficient and if the proposed improvements are feasible and economically profitable. The current distribution network in France has one distribution centre that serves around 30 customer’s warehouses. Since the products are voluminous and cheap the transportation cost has a considerable impact on margins. To keep the transportation costs under control the goods are usually manufactured near the demand, however a small volume of products is imported also from Eastern Europe, China, and the United States. Thus, the work focuses on improvements of the distribution network to reduce the transportation costs and the warehouse handling costs. In chapter 5 a Facility Location Problem (FLP) was developed with the intention of finding the optimal location for a warehouse to serve the French Market. The optimization problem is solved using the Generalized Reduced Gradient (GRG) method implemented in Microsoft Excel. The result of the study shows the current warehouse is very well located and the savings that can be achieved by relocating the operations do not justify the investment. In chapter 6 a feasibility study of increasing the number of warehouses from one to two was carried out and the problem was modelled as a multi-commodity p-median problem. The model was solved with both the GRG Method and an original implementation of the Genetic Algorithm and confirmed the opportunity of saving up to €45000 per month by adding a warehouse in the south of France in the Supply Network. Finally, in chapter 7, it was studied the opportunity of direct shipping some goods from a German factory to the French customers and a cross docking solution to reduce the transportation and handling costs. The project identifies the minimum number of pallets per truck to make direct shipment profitable. The study shows the solution delivers up to €120000 in savings per month in the best scenario making it extremely profitable.
TitulacióMÀSTER UNIVERSITARI EN CADENA DE SUBMINISTRAMENT, TRANSPORT I MOBILITAT (Pla 2014)
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tfm-klaidi-hasa-memoria.pdf | 2,450Mb | Accés restringit |