Branch-and-Cut for Computing Approximate Equilibria of Mixed-Integer Generalized Nash Games

Generalized Nash equilibrium problems with mixed-integer variables constitute an important class of games in which each player solves a mixed-integer optimization problem, where both the objective and the feasible set is parameterized by the rivals’ strategies. However, such games are known for failing to admit exact equilibria and also the assumption of all players being … Read more

Improving Directions in Mixed Integer Bilevel Linear Optimization

We consider the central role of improving directions in solution methods for mixed integer bilevel linear optimization problems (MIBLPs). Current state-of-the-art methods for solving MIBLPs employ the branch-and-cut framework originally developed for solving mixed integer linear optimization problems. This approach relies on oracles for two kinds of subproblems: those for checking whether a candidate pair … Read more

Data-Driven Optimization for Meal Delivery: A Reinforcement Learning Approach for Order-Courier Assignment and Routing at Meituan

The rapid growth of online meal delivery has introduced complex logistical challenges, where platforms must dynamically assign orders to couriers while accounting for demand uncertainty, courier autonomy, and service efficiency. Traditional dispatching methods, often focused on short-term cost minimization, fail to capture the long-term implications of assignment decisions on system-wide performance. This paper presents a … Read more

Political districting to maximize whole counties

We consider a fundamental question in political districting: How many counties can be kept whole (i.e., not split across multiple districts), while satisfying basic criteria like contiguity and population balance? To answer this question, we propose integer programming techniques based on combinatorial Benders decomposition. The main problem decides which counties to keep whole, and the … Read more

Discovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling

TitleDiscovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling Authorsİbrahim Oğuz Çetinkaya^1; İ. Esra Büyüktahtakın^1*; Parshin Shojaee^2; Chandan K. Reddy^2 Affiliations^1 Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA^2 Department of Computer Science, Virginia Tech, Arlington, VA, USA Abstract: Our study contributes to the scheduling and combinatorial optimization … Read more

Consolidation in Crowdshipping with Scheduled Transfer Lines: A Surrogate-Based Network Design Framework

Abstract: Crowdshipping has gained attention as an emerging delivery model thanks to advantages such as flexibility and an asset-light structure. Yet, it chronically suffers from a lackof mechanisms to create and exploit consolidation opportunities, limiting its efficiency and scalability. This work contributes to the literature in two ways: first, by introducing a novel consolidation concept … Read more

On vehicle routing problems with stochastic demands — Generic integer L-shaped formulations

We study a broad class of vehicle routing problems in which the cost of a route is allowed to be any nonnegative rational value computable in polynomial time in the input size. To address this class, we introduce a unifying framework that generalizes existing integer L-shaped (ILS) formulations developed for vehicle routing problems with stochastic … 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

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