J. Puerto, V. Blanco, M. A. Pozo, A. Torrejón Valenzuela
The cornerstone of any optimal decision problem: the objective function to be optimized. In your pretension, you may attempt to optimize measures of fairness, measures of position, dispersion or shape of the distribution of your data, measures of envy, measures of risk, robust measures. Everything as much as your imagination covers. In this work, we present a flexible framework relying on linear and integer-mixed mathematical programming models to implement a wide variety of measures in combinatorial optimization problems based on ordered and bilevel optimization techniques. Specifically, we remark its application to resource and facility location problems, but it also extends to other problems such as the well-known linear regression problem.
Keywords: Robust measures, combinatorial problems, quadratic programming, ordered optimization, bilevel problems.
Scheduled
Location (GELOCA3)
June 13, 2025 9:00 AM
Sala 3. Maria Rúbies Garrofé