Cut-based Conflict Analysis in Mixed Integer Programming

For almost two decades, mixed integer programming (MIP) solvers have used graph- based conflict analysis to learn from local infeasibilities during branch-and-bound search. In this paper, we improve MIP conflict analysis by instead using reasoning based on cuts, inspired by the development of conflict-driven solvers for pseudo- Boolean optimization. Phrased in MIP terminology, this type … Read more

Facets from solitary items for the 0/1 knapsack polytope

We introduce a new class of valid inequalities for any 0/1 knapsack polytope, called Solitary item inequality, which are facet-defining. We prove that any facet-defining inequality of a 0/1 knapsack polytope with nonnegative integral coefficients and right hand side 1 belongs to this class, and hence, the set of facet-defining inequalities corresponding to strong covers … Read more

Application of the Lovász-Schrijver Operator to Compact Stable Set Integer Programs

The Lov\’asz theta function $\theta(G)$ provides a very good upper bound on the stability number of a graph $G$. It can be computed in polynomial time by solving a semidefinite program (SDP), which also turns out to be fairly tractable in practice. Consequently, $\theta(G)$ achieves a hard-to-beat trade-off between computational effort and strength of the … Read more

Interdiction of minimum spanning trees and other matroid bases

In the minimum spanning tree (MST) interdiction problem, we are given a graph \(G=(V,E)\) with edge weights, and want to find some \(X\subseteq E\) satisfying a knapsack constraint such that the MST weight in \((V,E\setminus X)\) is maximized. Since MSTs of \(G\) are the minimum weight bases in the graphic matroid of \(G\), this problem … Read more

Factorized binary polynomial optimization

In binary polynomial optimization, the goal is to find a binary point maximizing a given polynomial function. In this paper, we propose a novel way of formulating this general optimization problem, which we call factorized binary polynomial optimization. In this formulation, we assume that the variables are partitioned into a fixed number of sets, and … Read more

The if-then Polytope: Conditional Relations over Multiple Sets of Binary Variables

Inspired by its occurrence as a substructure in a stochastic railway timetabling model, we study in this work a special case of the bipartite boolean quadric polytope. It models conditional relations across three sets of binary variables, where selections within two “if” sets imply a choice in a corresponding “then” set. We call this polytope … Read more

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) that does not impose additional specifications on the objective function or constraints. To enable this 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. … 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