Optimal counterfactual explanations for k-Nearest Neighbors using Mathematical Optimization and Constraint Programming

\(\) Within the topic of explainable AI, counterfactual explanations to classifiers have received significant recent attention. We study counterfactual explanations that try to explain why a data point received an undesirable classification by providing the closest data point that would have received a desirable one. Within the context of one the simplest and most popular … Read more

Hierarchically constrained multi-fidelity blackbox optimization

This work introduces a novel multi-fidelity blackbox optimization algorithm designed to alleviate the resource-intensive task of evaluating infeasible points. This algorithm is an intermediary component bridging a direct search solver and a blackbox, resulting in reduced computation time per evaluation, all while preserving the efficiency and convergence properties of the chosen solver. This is made … Read more

Incentivizing Investment and Reliability: A Study on Electricity Capacity Markets

The capacity market, a marketplace to exchange available generation capacity for electricity production, provides a major revenue stream for generators and is adopted in several U.S. regions. A subject of ongoing debate, the capacity market is viewed by its proponents as a crucial mechanism to ensure system reliability, while critics highlight its drawbacks such as … Read more

On a Tractable Single-Level Reformulation of a Multilevel Model of the European Entry-Exit Gas Market with Market Power

We propose a framework that allows to quantitatively analyze the interplay of the different agents involved in gas trade and transport in the context of the European entry-exit system. While previous contributions focus on the case of perfectly competitive buyers and sellers of gas, our novel framework considers the mathematically more challenging case of a … Read more

Bi-level multi-criteria optimization to include linear energy transfer into proton treatment planning

In proton therapy treatment planning, the aim is to ensure tumor control while sparing the various surrounding risk structures. The biological effect of the irradiation depends on both physical dose and linear energy transfer (LET). In order to include LET alongside physical dose in plan creation, we propose to formulate the proton treatment planning problem … Read more

Trajectory Optimization of Unmanned Aerial Vehicles in the Electromagnetic Environment

We consider a type of routing problems common in defence and security, in which we control a fleet of unmanned aerial vehicles (UAVs) that have to reach one or more target locations without being detected by an adversary. Detection can be carried out by a variety of sensors (radio receivers, cameras, personnel, etc) placed by … Read more

Solving the Traveling Telescope Problem with Mixed Integer Linear Programming

The size and complexity of modern astronomical surveys has grown to the point where, in many cases, traditional human scheduling of observations is tedious at best and impractical at worst. Automated scheduling algorithms present an opportunity to save human effort and increase scientific productivity. A common scheduling challenge involves determining the optimal ordering of a … Read more

Sequential Pricing of Electricity

This paper investigates the design and analysis of price formation in wholesale electricity markets given variability, uncertainty, non-convexity, and intertemporal operating constraints. The paper’s primary goal is to develop a framework to assess the many resource participation models, reserve product definitions, and enhanced pricing methods that have arisen in U.S. systems, especially in the context … Read more

Optimization and Simulation for the Daily Operation of Renewable Energy Communities

Renewable Energy Communities (RECs) are an important building block for the decarbonization of the energy sector. The concept of RECs allows individual consumers to join together in local communities to generate, store, consume and sell renewable energy. A major benefit of this collective approach is a better match between supply and demand profiles, and thus, … Read more

Resilient Relay Logistics Network Design: A k-Shortest Path Approach

Problem definition: We study the problem of designing large-scale resilient relay logistics hub networks. We propose a model of k-Shortest Path Network Design, which aims to improve a network’s efficiency and resilience through its topological configuration, by locating relay logistics hubs to connect each origin-destination pair with k paths of minimum lengths, weighted by their … Read more