Colombian University Optimizes Coffee Supply with Xpress

Blog Post created by Advocate on Mar 23, 2017

Medaglia Pic.jpgDoctor Andrés L. Medaglia is a professor in the Department of Industrial Engineering’s Center for Optimization and Applied Probability (COPA, for its Spanish acronym) at Universidad de los Andes, Colombia. As an active member of the FICO Academic Partner Program (APP), Dr. Medaglia and his students have complimentary access to FICO Xpress Optimization Suite to solve real world problems and conduct meaningful research.


"For me one of the strongest features of Xpress is its flexibility to have a wide range of uses and users with different abilities."

Doctor Andrés L. Medaglia, Universidad de los Andes, Colombia


COPA helps organizations in Latin America better design and improve their systems using advanced analytics. Their work involves a wide range of systems from health to infrastructure. However, despite the fast pace of growth in the region, many companies continue to lack the analytical power to solve the variety of complex new challenges that continually arise.


Medaglia started using Xpress back in 2002. At the time, he was a very strong and avid user of AMPL, and while he still thinks it is an adequate modeling language, he was thrilled when he first used Xpress. The elegant architecture allowed him to play different roles in the development process of optimization-based decision support systems, and that caught his attention.


One of the first problems he solved with Xpress required slimming down the Colombian coffee supply network, while continuing to provide a high level of service to the coffee growers. The report is titled Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example, and the abstract describes the project as follows:


Coffee Picture.jpg"The Colombian coffee supply network, managed by the Federación Nacional de Cafeteros de Colombia (Colombian National Coffee-Growers Federation), requires slimming down operational costs while continuing to provide a high level of service in terms of coverage to its affiliated coffee growers. We model this problem as a biobjective (cost-coverage) uncapacitated facility location problem (BOUFLP). We designed and implemented three different algorithms for the BOUFLP that are able to obtain a good approximation of the Pareto frontier. We designed an algorithm based on the Nondominated Sorting Genetic Algorithm; an algorithm based on the Pareto Archive Evolution Strategy; and an algorithm based on mathematical programming. We developed a random problem generator for testing and comparison using as reference the Colombian coffee supply network with 29 depots and 47 purchasing centers. We compared the algorithms based on the quality of the approximation to the Pareto frontier using a nondominated space metric inspired on Zitzler and Thiele's. We used the mathematical programming-based algorithm to identify unique tradeoff opportunities for the reconfiguration of the Colombian coffee supply network. Finally, we illustrate an extension of the mathematical programming-based algorithm to perform scenario analysis for a set of uncapacitated location problems found in the literature."


While that is just one project in which Xpress was used, COPA students and researchers have worked on over 30 Xpress related projects. Medaglia likes to use Xpress for its flexibility. What captured his attention was “the nice and elegant architecture that allowed [him] to play different roles in the development process of optimization-based decision support systems.” The powerful Mosel language on Xpress-IVE provides a friendly development environment for teaching beginners. “Stepping up the ladder, in a more advanced (or research-oriented) setting, [he] use[s] the iterative capability of Mosel that goes beyond a declarative language.” These features are quite useful for developing “more complex solutions that require advanced decomposition techniques, column generation, or the use of callbacks to customize the branch-and-bound procedure.” Then, after the prototyping phase when performance is of the utmost importance, one can always “rely on invoking the optimizer from a general-purpose language like Java.”


Xpress Optimization Suite enables operations research professionals, analysts, and consultants to quickly find the mathematically best solution for industry problems. Students and researchers at COPA have been using Xpress for 14 years. Medaglia notes that “it is always comforting to see how well the Xpress-MP optimization engine has evolved with the years.” When evaluating FICO’s complete optimization suite, Medaglia praises the advantages of using a flexible framework on top of a very strong engine.


You too can benefit from the power, flexibility, and ease-of-use that Xpress offers. More information here: