Stochastic Queens Elimination

This research introduces the Stochastic Sequential Queens Elimination Problem, where on the \(n\)-queens board, each activated queen simultaneously attempts to eliminate all queens in her unblocked neighborhood, each independently succeeding with probability \(p\). The objective is to minimize the expected cumulative conflict count over the trajectory. This research proposes a Markov decision process for this … Read more

Polyhedral Bounds for Forbidden-Vertices Sets and No-Good Cut Relaxations

We study the convex hull obtained after deleting prescribed vertices from the binary cube. The analysis separates three regimes according to the number of deleted vertices. When this number is fixed, both the original-space facet count and the linear extension complexity remain linear in the ambient dimension, up to constants depending only on the number … Read more

Spatial Optimization Models for Width-Constrained Wildlife Corridor Design

Human activities increasingly fragment natural habitats, placing many species at risk of population decline. This creates an urgent need to preserve biodiversity and maintain ecological connectivity through wildlife corridors. We present two spatial optimization models for corridor design that explicitly incorporate corridor width as a key ecological criterion. The first model minimizes total corridor cost … Read more

Robust Network Design for Potential-Based Flows with Controllable Elements

We study adjustable robust network design for potential-based flows with controllable elements under load uncertainty. The resulting problem combines discrete here-and-now expansion decisions with wait-and-see operational decisions governed by nonconvex flow constraints. Moreover, controllable elements introduce adjustable integer decisions, which are algorithmically challenging. We equivalently characterize robust feasibility and robust optimality of a fixed network … Read more

When do Mixed-Integer Games Admit Rational Equilibria?

We consider mixed-integer linear-quadratic generalized Nash equilibrium problems, i.e., games in which each player solves a mixed-integer program subject to linear constraints in her own and rivals’ strategies as well as an objective which is quadratic in her own strategies and bilinear in her own and rivals’ strategies. For this class of games, we study … Read more

Advancing Branch-and-Price for Graph Coloring: New Pricing Strategies and Benchmark Results

This paper proposes BPCOL+, an exact branch-and-price algorithm for the Graph Coloring Problem. The algorithm is both novel and highly effective, integrating enhanced pricing strategies within Zero-Suppressed Binary Decision Diagrams (ZDDs) to efficiently solve the pricing problem associated with the maximal-stable-set-based set-covering formulation. After computing upper and lower bounds at the root node using heuristic … Read more

Exact Approaches for the Maximum Mortality Rate Clique Problem

This paper develops exact solution methods for the maximum mortality rate clique problem, which aims to identify a cluster of diseases in a comorbidity graph associated with the highest mortality rate among patients whose healthcare encounters are recorded in electronic health records. We establish the NP-hardness of the problem and propose two mixed-integer linear programming … Read more

Relief-based Anesthesiologist Scheduling with Stochastic Surgery Durations

We present a two-stage stochastic programming model for scheduling anesthesiologists to operating rooms under uncertainty in surgery durations. The proposed model takes a relief order to balance anesthesiologists’ workload as input and captures the trade-offs between anesthesiologist relief times, handoffs and under-staffing. To address the computational challenges of solving the proposed model, we derive supervalid … Read more

Objective Domain Reduction for Enhancing Solver Performance on Challenging Integer Programs

In this study, we explore how the domain of objective function values for challenging integer programs can be reduced and whether such a reduction can improve the solution process. Our work is motivated by binary search, a technique that efficiently narrows a search space by repeatedly halving it through feasibility checks. Building on this idea, … Read more