A. Torrejon, I. Ljubic, J. Puerto

Ensuring fairness in optimization-based decision problems is increasingly critical across diverse applications. In this talk, we present a novel framework that integrates ordered optimization and bilevel programming to model and solve fair decision-making problems. Our approach allows the direct optimization of fairness measures while maintaining overall efficiency and feasibility. In this work, we illustrate the framework’s flexibility by applying it to vehicle routing, facility location, and linear regression estimation problems. Computational experiments highlight trade-offs between fairness and performance, and show how bilevel formulations capture hierarchical decision-making aspects inherent in real-world networks.

Keywords: Fairness, Order Optimization, Bilevel Optimization

Scheduled

GT GELOCA IV: Stochastic optimization and fairness in location and routing
September 4, 2026  3:30 PM
Aula B


Other papers in the same session


Cookie policy

We use cookies in order to be able to identify and authenticate you on the website. They are necessary for the correct functioning of it, and therefore they can not be disabled. If you continue browsing the website, you are agreeing with their acceptance, as well as our Privacy Policy.

Additionally, we use Google Analytics in order to analyze the website traffic. They also use cookies and you can accept or refuse them with the buttons below.

You can read more details about our Cookie Policy and our Privacy Policy.