A Polyhedral Characterization of Linearizable Quadratic Combinatorial Optimization Problems

We introduce a polyhedral framework for characterizing instances of quadratic combinatorial optimization programs (QCOPs) that are linearizable, meaning that the quadratic objective can be equivalently rewritten as linear in such a manner that preserves the objective function value at all feasible solutions. In particular, we show that an instance is linearizable if and only if … Read more

Binary Integer Program Reformulation: A Set System Approximation Approach

This paper presents a generic reformulation framework for binary integer programs (BIPs) without imposing additional specifications for the objective function or constraints. To facilitate such generality, we introduce a set system approximation theory designed to identify the tightest inner and outer approximations for any binary solution space using special types of set systems. This development … Read more

Structural Insights and an IP-based Solution Method for Patient-to-room Assignment Under Consideration of Single Room Entitlements

Patient-to-room assignment (PRA) is a scheduling problem in decision support for large hospitals. This work proposes Integer Programming (IP) formulations for dynamic PRA, where either full, limited or uncertain information on incoming patients is available. The applicability is verified through a computational study. Results indicate that large, real world instances can be solved to a … Read more

QUBO Dual Bounds via SDP Plane Projection Method

In this paper, we present a new method to solve a certain type of Semidefinite Programming (SDP) problems. These types of SDPs naturally arise in the Quadratic Convex Reformulation (QCR) method and can be used to obtain dual bounds of Quadratic Unconstrained Binary Optimization (QUBO) problems. QUBO problems have recently become the focus of attention … Read more

An Exceptionally Difficult Binary Quadratic Optimization Problem with Symmetry: a Challenge for The Largest Unsolved QAP Instance Tai256c

Tai256c is the largest unsolved quadratic assignment problem (QAP) instance in QAPLIB. It is known that QAP tai256c can be converted into a 256 dimensional binary quadratic optimization problem (BQOP) with a single cardinality constraint which requires the sum of the binary variables to be 92. As the BQOP is much simpler than the original … Read more

Branch-and-Bound versus Lift-and-Project Relaxations in Combinatorial Optimization

In this paper, we consider a theoretical framework for comparing branch-and-bound with classical lift-and-project hierarchies. We simplify our analysis of streamlining the definition of branch-and-bound. We introduce “skewed $k$-trees” which give a hierarchy of relaxations that is incomparable to that of Sherali-Adams, and we show that it is much better for some instances. We also … Read more

Affine FR : an effective facial reduction algorithm for semidefinite relaxations of combinatorial problems

\(\) We develop a new method called \emph{affine FR} for recovering Slater’s condition for semidefinite programming (SDP) relaxations of combinatorial optimization (CO) problems. Affine FR is a user-friendly method, as it is fully automatic and only requires a description of the problem. We provide a rigorous analysis of differences between affine FR and the existing … Read more

Improving Conflict Analysis in MIP Solvers by Pseudo-Boolean Reasoning

Conflict analysis has been successfully generalized from Boolean satisfiability (SAT) solving to mixed integer programming (MIP) solvers, but although MIP solvers operate with general linear inequalities, the conflict analysis in MIP has been limited to reasoning with the more restricted class of clausal constraint. This is in contrast to how conflict analysis is performed in … Read more

Recycling Valid Inequalities for Robust Combinatorial Optimization with Budget Uncertainty

Robust combinatorial optimization with budget uncertainty is one of the most popular approaches for integrating uncertainty into optimization problems. The existence of a compact reformulation for (mixed-integer) linear programs and positive complexity results give the impression that these problems are relatively easy to solve. However, the practical performance of the reformulation is quite poor when … Read more