The subtle behavior of the facial distance

We give a simple example that disproves the following 2015 conjecture of Lacoste-Julien and Jaggi concerning the pyramidal width (aka facial distance): The pyramidal width of a set of vertices is non-increasing when another vertex is added (assuming that all previous points remain vertices). In contrast to the recent example by Zhao (arXiv:2607.29555), our counterexample … Read more

An Asymptotic Framework for the Integrality Gap of the Traveling Salesman Problem

The integrality gap of the subtour elimination relaxation for the Traveling Salesman Problem is a longstanding open problem, epitomized by the \(\frac{4}{3}\)-conjecture. Understanding this gap requires a detailed analysis of the extreme points of the subtour elimination polytope. In this work, we introduce a new perspective for studying the integrality gap through what we call … Read more

The Integrality Gap of the Traveling Salesman Problem is 4/3 if the LP Solution Has at Most n+8 Non-Zero Components

We address the classical Dantzig – Fulkerson – Johnson formulation of the symmetric metric Traveling Salesman Problem and study the integrality gap of its linear relaxation, namely the Subtour Elimination Problem (SEP). This integrality gap is conjectured to be 4/3. We prove that, when solving a problem on n nodes, if the optimal SEP solution … Read more

Solving Quasi-Variational Inequalities Using the Progressive Decoupling of Linkages

Inspired by the progressive decoupling of linkages methodology for optimization and variational inequalities, we propose an algorithm for solving quasi-variational inequalities as a sequence of variational inequalities. Our method is shown to converge locally under some regularity conditions and globally when such conditions hold throughout the entire domain. Separately, under other type of assumptions, global … Read more

An Adaptive Augmented Lagrangian Method for Deterministic and Stochastic Nonconvex Optimization

We present an inexact Augmented Lagrangian algorithm for solving nonlinear, non-convex optimization problems. Unlike most recently proposed Augmented Lagrangian methods with worst-case complexity guarantees, we utilize adaptive penalty parameter updates and full dual stepsizes. We show that the method matches the best known worst-case complexity results for Augmented Lagrangian methods (up to logarithmic factors) when … Read more

Optimizing Family Medicine Residency Schedules under the Clinic First Principles

Family medicine residency programs must balance educational and operational requirements while providing residents with consistent exposure to continuity clinics, a central principle of the Clinic First Model. We study the Family Medicine Residency Scheduling problem and develop a binary integer programming (BIP) framework that incorporates Clinic First principles through two criteria: Clinic Time Consistency (CTC), … Read more

Sharp Singularity-Degree Bounds for Equality-Generated SDP–RLT Relaxations of Binary Programs

Singularity degree is an important measure of semidefinite programming (SDP) degeneracy, but it is generally unavailable a priori from the problem data. We augment the Shor relaxation of binary sets \(\{x\in\{0,1\}^n:Ax=b\}\) with the first-level Reformulation–Linearization Technique (RLT) equations generated by the defining linear equalities. For the resulting equality-generated SDP–RLT relaxation, we determine the exact worst-case … Read more

Valid Inequalities for Potential-Based Network Design Including Compressors

We study the steady-state expansion problem for potential-based flow networks. Constructing a cost-minimal network that admits a flow satisfying the underlying physical laws is a central problem in the design of gas, hydrogen, water, and electricity infrastructures. The physical behavior of such networks is governed by nonlinear relations between arc flows and the potential differences … Read more

ArcLP: A Matlab implementation of an O(√nL) arc-search infeasible interior-point algorithm for linear programming

This paper presents a Matlab implementation of an arc-search infeasible interior point algorithm for linear programming (LP), which has a proven polynomial bound of O(√nL), the best among all interior-point algorithms for LP. Software architecture and major functions are discussed. Its ease of use is described by a simple example. Crucial strategies are summarized. Quality … Read more