The opioid crisis has remained a major public health challenge in the United States for many years. This study develops a data-driven decision support framework to guide policymakers in allocating county-level budgets across multiple expenditure categories in order to address the opioid crisis. We compile and curate a detailed dataset on fiscal policy and opioid-related … Read more
Given a set of train routes with route costs and a set of compatible route pairs with pairing costs, the Train Single-Routing Selection Problem (TSRSP) seeks to assign one route to each train, minimizing the total cost while ensuring pairwise compatibility among the selected routes. This problem is of significant practical relevance in rail traffic … Read more
This study addresses the problem of minimizing the weighted completion time variance (WCTV) in single-machine scheduling. Unlike the unweighted version, which has been extensively studied, the weighted variant introduces unique challenges due to the absence of theoretical properties that could guide the design of efficient algorithms. We propose a mathematical programming framework based on a … Read more
We present a two-stage stochastic programming model for optimizing anesthesiologist schedules, explicitly accounting for uncertainty in surgery durations and anesthesiologist handoffs. To inform model design, we conducted an online survey at our partner institution to identify key factors affecting the quality of intraoperative anesthesiologist handoffs. Insights from the survey results are incorporated into the model, … Read more
In this paper, we address the problem of allocating and scheduling employees for work shifts in the pharmacy sector of a private hospital. To tackle this issue, we introduce the pharmacy staff scheduling problem (PSSP) in the literature. To solve the problem, we propose a mixed-integer programming formulation that considers various aspects, such as the … Read more
There is a growing need to expand and strengthen the industrial engineering/operations research workforce. Undergraduate research experiences are an effective way to build in-demand skills and to attract people to science, technology, engineering, and mathematics fields, such as industrial engineering/operations research. However, the traditional apprenticeship model of an undergraduate research experience limits the number of … Read more
This paper presents scalable algorithms for computing pure Nash equilibria (PNEs) in large-scale integer programming games (IPGs), where existing exact methods typically handle only small numbers of players. Motivated by a county-level aquatic invasive species (AIS) prevention problem with 84 decision makers, we develop and analyze random-restart best-response dynamics (RR-BRD), a randomized search framework for … Read more
Limited geographic access to obstetric care prevents some pregnant people from receiving timely and risk-appropriate services. This challenge is especially acute in rural areas, where rural residents often travel far distances to obstetric care. Furthermore, obstetric access is worsening due to the growing number of closures of rural hospitals’ obstetric units, often due to financial … Read more
For agent based micro simulations, as used for example for epidemiological modeling during the COVID-19 pandemic, a realistic base population is crucial. Beyond demographic variables, health-related variables should also be included. In Germany, health-related surveys are typically small in scale, which presents several challenges when generating these variables. Specifically, strongly imbalanced classes and insufficient … Read more
The problem of approximation by piecewise affine functions has been studied for several decades (least squares and uniform approximation). If the location of switches from one affine piece to another (knots for univariate approximation) is known the problem is convex and there are several approaches to solve this problem. If the location of such switches … Read more