Stochastic home care transportation with dynamically prioritized patients: An integrated facility location, fleet sizing, and routing approach
CME Department Seminar
August 25, 2025
10:00 AM - 11:00 AM America/Chicago
Presenter: Yong-Hong Kuo, PhD, University of Hong Kong
Location: ERF Room 1047
Abstract: We study a home health care (HHC) problem that is characterized by prioritized patients and uncertain demands. In practice, HHC supply chain networks often struggle to meet high demand due to a shortage of service vehicles. Additionally, disruptions caused by natural calamities and pandemics (e.g., COVID-19) further compound these challenges, necessitating the consideration of real-life characteristics such as patient priorities, infrastructure locations, and transportation of medical supplies with uncertain demands. To formulate the problem, we propose a multi-depot and multi-period chance-constrained optimization model with precedence constraints, assuming that the demand quantities for medical supplies are random variables. Since patients’ medical conditions vary in severity, the priority of each patient is translated into a time-dependent potential healthcare cost that changes dynamically over the planning horizon. The solution to the proposed model determines the optimal locations for the base Mobile Health Facilities (MHFs) and the fleet size of HHC vehicles, and generates scheduling and routing plans to visit patients within specified time windows. We propose a unique three-phase solution approach, integrated with stochastic simulation, to address the problem. We then assess the robustness of the proposed model based on a realistic case of HHC service provision in Hong Kong and explore the optimal values for two model parameters, namely the Vehicle Threshold Index and the MHF Threshold Index. The performance evaluation tests show that the proposed solution method is efficient and effective for solving real-world problems. This is a joint work with Jamal Abdul Nasir.
Speaker Bio: Yong-Hong Kuo is an associate professor in the Department of Data and Systems Engineering at the University of Hong Kong. He earned his B.Sc. in mathematics and M.Phil. and Ph.D. in systems engineering and engineering management from the Chinese University of Hong Kong. Kuo's research focus is on the integration of systems modeling, discrete optimization, and data engineering for solving decision-making problems in service systems, particularly in logistics, transportation, and healthcare services. He has served the Operational Research Society of Hong Kong as president (2023 - 2024) and the Association of Asia-Pacific Operational Research Societies as vice president. He is department editor for IEEE Transactions on Engineering Management and associate editor for Operations Research, Data Analytics and Logistics (formerly Operations Research for Health Care), and on the editorial boards of Decision Sciences and Transportation Research Part E.
Date posted
Aug 20, 2025
Date updated
Aug 20, 2025