Single-Scenario Facet Preservation for Stochastic Mixed-Integer Programs

We consider improving the polyhedral representation of the extensive form of a stochastic mixed-integer program (SMIP). Given a facet for a single-scenario version of an SMIP, our main result provides necessary and sufficient conditions under which this inequality remains facet-defining for the extensive form. We then present several implications, which show that common recourse structures … Read more

Partitioning a graph into low-diameter clusters

This paper studies the problems of partitioning the vertices of a graph G = (V,E) into (or covering with) a minimum number of low-diameter clusters from the lenses of approximation algorithms and integer programming. Here, the low-diameter criterion is formalized by an s-club, which is a subset of vertices whose induced subgraph has diameter at … Read more

On the Complexity of Finding Locally Optimal Solutions in Bilevel Linear Optimization

\(\) We consider the theoretical computational complexity of finding locally optimal solutions to bilevel linear optimization problems (BLPs), from the leader’s perspective. We show that, for any constant \(c > 0\), the problem of finding a leader’s solution that is within Euclidean distance \(c^n\) of any locally optimal leader’s solution, where \(n\) is the total … Read more

Column Elimination: An Iterative Approach to Solving Integer Programs

We present column elimination as a general framework for solving (large-scale) integer programming problems. In this framework, solutions are represented compactly as paths in a directed acyclic graph. Column elimination starts with a relaxed representation, that may contain infeasible paths, and solves a constrained network flow over the graph to find a solution. It then … Read more

Integrated Optimization of Timetabling and Electric Vehicle Scheduling: A Case Study of Aachen, Germany

We tackle the integrated planning problem of periodic timetabling and electric vehicle scheduling, crucial for cities transitioning to electric bus fleets. Given existing timetables, we allow only minor modifications and propose an iterative solution approach that addresses the Electric Vehicle Scheduling Problem (EVSP) in each iteration. Due to the NP-hard nature of EVSP, we employ … Read more

Advances in Polyhedral Relaxations of the Quadratic Linear Ordering Problem

We report on results concerning the polyhedral structure of the quadratic linear ordering problem and its associated integer linear programming formulations. Specifically, we provide a deeper analysis of the characteristic equation system that partly describes the corresponding polytope, i.e., the convex hull of the feasible solutions to the quadratic linear ordering problem, and determine an … Read more

Hybrid iterated local search algorithm for the vehicle routing problem with lockers

In the Vehicle Routing Problem (VRP) with Lockers, the vertices in a graph are divided into two key subsets: a customer set and a locker set, with lockers serving as alternative delivery points for the customer’s parcel. This paper presents a generic VRP with lockers, where a customer’s parcel can be delivered either to its … Read more

An Introduction to Decision Diagrams for Optimization

This tutorial provides an introduction to the use of decision diagrams for solving discrete optimization problems. A decision diagram is a graphical representation of the solution space, representing decisions sequentially as paths from a root node to a target node. By merging isomorphic subgraphs (or equivalent subproblems), decision diagrams can compactly represent an exponential solution … Read more

The Dantzig-Fulkerson-Johnson TSP formulation is easy to solve for few subtour constraints

The most successful approaches for the TSP use the integer programming model proposed in 1954 by Dantzig, Fulkerson, and Johnson (DFJ). Although this model has exponentially many subtour elimination constraints (SECs), it has been observed that relatively few of them are needed to prove optimality in practice. This leads us to wonder: What is the … Read more

The Augmented Factorization Bound for Maximum-Entropy Sampling

The maximum-entropy sampling problem (MESP) aims to select the most informative principal submatrix of a prespecified size from a given covariance matrix. This paper proposes an augmented factorization bound for MESP based on concave relaxation. By leveraging majorization and Schur-concavity theory, we demonstrate that this new bound dominates the classic factorization bound of Nikolov (2015) and a recent … Read more