A Data-Driven County-Level Budget Allocation Model for Opioid Crisis Management: Insights from West Virginia

Problem definition. 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. Methodology/results. We compile and curate a detailed dataset on fiscal … Read more

Anesthesiologist Scheduling with Handoffs: A Combined Approach of Optimization and Human Factors

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

A Branch and Price Algorithm for Scheduling in Surgery Pre-admission Testing Clinics

A Surgery Pre-Admission Testing (PAT) clinic is a hospital unit designed to serve pre-operative patients by gathering critical patient information and performing procedure-specific tests to prepare them for surgery. Patients may require multiple tests, each conducted by a specialized nurse. A patient must be assigned to a room before starting any test and must stay … Read more

A Two-stage Stochastic Programming Approach for CRNA Scheduling with Handovers

We present a two-stage stochastic integer program for assigning Certified Registered Nurse Anesthetists (CRNAs) to Operating Rooms (ORs) under surgery duration uncertainty. The proposed model captures the trade-offs between CRNA staffing levels, CRNA handovers and under-staffing in the ORs. Since the stochastic program includes binary variables in both stages, we present valid inequalities to tighten … Read more

Mixed Integer Linear Programming Formulations for Robust Surgery Scheduling

We introduce Mixed Integer Linear Programming (MILP) formulations for the two-stage robust surgery scheduling problem (2SRSSP). We derive these formulations by modeling the second-stage problem as a longest path problem on a layered acyclic graph and subsequently converting it into a linear program. This linear program is then dualized and integrated with the first-stage, resulting … Read more