On the integrality gap of the Complete Metric Steiner Tree Problem via a novel formulation

In this work, we study the metric Steiner Tree problem on graphs focusing on computing lower bounds for the integrality gap of the bi-directed cut (BCR) formulation and introducing a novel formulation, the Complete Metric (CM) model, specifically designed to address the weakness of the BCR formulation on metric instances. A key contribution of our … Read more

Relay-Hub Network Design for Consolidation Planning Under Demand Variability

Problem description: We study the problem of designing large-scale resilient relay logistics hub networks. We propose a model of Capacitated Relay Network Design under Stochastic Demand and Consolidation-Based Routing (CRND-SDCR), which aims to improve a network’s efficiency and resilience against commodity demand variability through integrating tactical decisions. Methodology: We formulate CRND-SDCR as a two-stage stochastic … Read more

Solving the parallel processor scheduling and bin packing problems with contiguity constraints: mathematical models and computational studies

The parallel processor scheduling and bin packing problems with contiguity constraints are important in the field of combinatorial optimization because both problems can be used as components of effective exact decomposition approaches for several two-dimensional packing problems. In this study, we provide an extensive review of existing mathematical formulations for the two problems, together with … Read more

Extended Formulations for Control Languages Defined by Finite-State Automata

Many discrete optimal control problems feature combinatorial constraints on the possible switching patterns, a common example being minimum dwell-time constraints. After discretizing to a finite time grid, for these and many similar types of constraints, it is possible to give a description of the convex hull of feasible (finite-dimensional) binary controls via extended formulations. In … Read more

Edge expansion of a graph: SDP-based computational strategies

Computing the edge expansion of a graph is a famously hard combinatorial problem for which there have been many approximation studies. We present two variants of exact algorithms using semidefinite programming (SDP) to compute this constant for any graph. The first variant uses the SDP relaxation first to reduce the search space considerably. The problem … Read more

On Packing a Submodular Knapsack of Unknown Capacity

Consider the problem of maximizing a monotone-increasing submodular function defined on a set of weighted items under an unknown knapsack capacity. Assume that items are packed sequentially into the knapsack and that the capacity of the knapsack is accessed through an oracle that answers whether an item fits into the currently packed knapsack. If an … Read more

The Bipartite Implication 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 implying sets imply a choice in a corresponding implied set. We call this polytope … Read more

The Multi-Stop Station Location Problem: Exact Approaches

The multi-stop station location problem (MSLP) aims to place stations such that a set of trips is feasible with respect to length bounds while minimizing cost. Each trip consists of a sequence of stops that must be visited in a given order, and a length bound that controls the maximum length that is possible without … Read more

New cuts and a branch-cut-and-price model for the Multi Vehicle Covering Tour Problem

The Multi-Vehicle Covering Tour Problem (m-CTP) involves a graph in which the set of vertices is partitioned into a depot and three distinct subsets representing customers, mandatory facilities, and optional facilities. Each customer is linked to a specific subset of optional facilities that define its coverage set. The goal is to determine a set of … Read more

Network Flow Models for Robust Binary Optimization with Selective Adaptability

Adaptive robust optimization problems have received significant attention in recent years, but remain notoriously difficult to solve when recourse decisions are discrete in nature. In this paper, we propose new reformulation techniques for adaptive robust binary optimization (ARBO) problems with objective uncertainty. Without loss of generality, we focus on ARBO problems with “selective adaptability”, a … Read more