Optimizing Product Transportation from Hispanic Markets

May 15th, 2012

Client: Frito Laygamesa__2006_-logo-cb8481d8e4-seeklogocom
Team: Javier Gonzalez, Fernando Sada, Marcelo Sada
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation

In order to satisfy the large Hispanic market in the United States, Frito Lay imports products manufactured in Mexico by Gamesa, a sister company to Frito Lay due to the fact that they are both owned by PepsiCo. Gamesa has plants all across Mexico, having the main ones located in Celaya, Vallejo, Obregon and Monterrey. In the past, all products being imported into the U.S were produced in Obregon, a city in Northwestern Mexico. As of today, the Hispanic population has dispersed all across the country, increasing Gamesa’s market to a large portion of it. Gamesa’s products are now being distributed all the way from California, to Texas, and onto the East Coast and Midwest. Imports have increased so much that in order to satisfy the demand, Gamesa has started producing all across Mexico for exports.

Currently, all trucks that move products from distinct parts of Mexico into the U.S border pass through Obregon. Although this is convenient for deliveries to California, it might not be optimal for deliveries in other regions. Therefore, our project goal is to help Frito Lay reduce transportation costs of certain products by finding the optimal routes to export/import from Mexico into the United States. This of course is based on the demand and production of the different products, which differ in great amounts.

To achieve the results we evaluated the current transportation method used by Frito Lay. We analyzed products, volumes, demands, routes and destinations to determine if it could be improved or not, and if so, how. We created a Multi-Commodity Fixed Charge Network Flow Model and used two computational packages called AMPL and CPLEX to find the optimal route. The results indicated that new routes should be considered for optimality and ultimately be able to reduce costs.

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