A linearly convergent algorithm for variational inequalities based on fiber bundle

The variational inequality (VI) problem is a fundamental mathematical framework for many classical problems. This paper introduces an algorithm that applies to arbitrary finite-dimensional VIs with general compact convex sets and general continuous functions. The algorithm guarantees global linear convergence to an approximate solution without requiring any assumptions, including the typical monotonicity. Our approach adapts … Read more

MDP modeling for multi-stage stochastic programs

We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes structured MDPs with continuous state and action spaces. We extend policy graphs to include decision-dependent uncertainty for one-step transition probabilities as well as a limited form of statistical learning. We focus on the expressiveness of … Read more

An extension of an interior-point method to include risk aversion in large-scale multistage stochastic optimization

In the earlier paper “On solving large-scale multistage stochastic optimization problems with a new specialized interior-point approach, European Journal of Operational Research, 310 (2023), 268–285” the authors presented a novel approach based on a specialized interior-point method (IPM) for solving (risk neutral) large-scale multistage stochastic optimization problems. The method computed the Newton direction by combining … Read more

Approximating value functions via corner Benders’ cuts

We introduce a novel technique to generate Benders’ cuts from a conic relaxation (“corner”) derived from a basis of a higher-dimensional polyhedron that we aim to outer approximate in a lower-dimensional space. To generate facet-defining inequalities for the epigraph associated to this corner, we develop a computationally-efficient algorithm based on a compact reverse polar formulation … Read more

Approximating inequality systems within probability functions: studying implications for problems and consistency of first-order information

In this work, we are concerned with the study of optimization problems featuring so-called probability or chance constraints. Probability constraints measure the level of satisfaction of an underlying random inequality system and ensure that this level is high enough. Such an underlying inequality system could be expressed by an abstractly known or perhaps costly to … Read more

Drone Station Location and Routing Optimization for Infrastructure Inspection

Recent advancements in drone technology have expanded drone applications in logistics, humanitarian aid, and infrastructure surveillance. Motivated by the demand for drone-based infrastructure inspection and the emerging design of drone battery swapping stations, this paper introduces the location routing problem with heterogeneous stations and drones (LRPHSD). In the problem, two types of stations are considered: … Read more

Solution of Stochastic Facility Location Problems with Combinatorially many Decision-Dependent Distributions

This article describes a model and an exact solution method for facility location problems with decision-dependent uncertainties. The model allows characterizing the probability distribution of the random elements as a function of the choice of open facilities. This, in turn, generates a combinatorial number of potential distributions of the random elements. Though general in the … Read more

Measuring the Economic Value of Wind–Solar Complementarity in Europe Using Chance Constraints

The variability of wind and solar photovoltaic (PV) generation poses significant risks for producers in day-ahead electricity markets, where commitments must be made before actual output is realized. A common mitigation strategy is to invest in storage, but an alternative is to exploit the natural complementarity between wind and solar resources. We evaluate this economic … Read more

A two-stage optimization approach for selecting electric-flight airports

The decarbonization of short-haul air transport has gained increasing attention, with electric aircraft emerging as a promising alternative to conventional short-haul aviation. However, given the substantial investment anticipated for the necessary infrastructure, a strategic and globally coordinated selection of airports is imperative. The aim of this paper is to address this problem and determine the … Read more

Final Exam Scheduling at Bucknell University: A Case Study and Open-Source Tool

Problem Definition: Final exam scheduling is a common but challenging optimization problem. At Bucknell University, a small liberal arts institution, the problem is particularly complex and has historically required the Registrar’s Office to spend months manually designing an exam schedule each semester. Methodology: We worked in close collaboration with the Registrar’s Office. First, we created … Read more