Mancuso, Andrea (2023) Optimizing Healthcare Logistics: Innovative Models, Methods, and Applications for Location, Scheduling, and Routing. [Tesi di dottorato]

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Abstract

This Ph.D. thesis explores the application of Information and Communication Technology (ICT) in healthcare logistics, assessing its potential to rationalize operations. At its core, this research primarily focuses on application of Operational Research methods to improve the efficiency and reliability of healthcare systems. Before assessing specific problem arising from real world, this study offers an overview of the existing work in the field. Specifically, it highlights the key contributions and the potential for optimization enabled by technological progress. Following this, the thesis progresses to its core scientific contribution, tackling a challenge identified within the context of Facility Location problems, specifically focusing on the strategic management of the Blood Supply Chain. This study introduces two modeling frameworks: a case-based and a scenario-based approach. Both are modeled using hard and soft constraints to represent real-world conditions that should be adhered to. The objective is to balance donor self-sufficiency with cost minimization in system management. The scenario-based formulation is presented in two variations: an average-case and a worst-case scenario, to address the sensitivity of the solution to perturbations in conditions. The effectiveness of this approach is confirmed by a broad experimentation on a real case study in the Italian regions of Campania, Puglia, and Lombardy. After exploring Facility Location, the thesis shifts its attention to surgery scheduling, addressing the challenges of Integrated Operating Room Planning and Scheduling faced by hospitals. It introduces a tool based on two Integer Linear Programs (ILPs) designed to optimize surgical schedules. The tool aims to balance the maximization of performed elective surgeries with the management of emergency operations. The first ILP aims to enhance room occupancy, considering the potential arrival of emergencies that must be promptly integrated into the schedule, thereby providing an initial plan for the surgical department. The second ILP operates in real time, re-optimizing the schedule whenever there is a deviation from the planned activities, such as surgeries lasting longer than expected or the arrival of an emergency case. This ensures efficiency and responsiveness throughout the entire planning horizon. The effectiveness of these models is further underscored by their application to real world data from a hospital in Naples. Additionally, the thesis investigates the field of drone logistics, focusing on potential application in healthcare delivery. It introduces an innovative Mixed-Integer Linear Programming model to address the Flying Sidekick Traveling Salesman Problem, employing a Branch and Cut approach. This method advances the field by representing the state of the art. This exploration not only provides a new methodology to the existing literature but also opens to further research in healthcare logistics, especially concerning the use of drones for efficient and timely delivery. In conclusion, this thesis covers a wide range of Operational Research applications in healthcare. It exploits issues ranging from strategic planning and policy development to practical and logistical enhancements, providing a perspective on the potential and solutions in healthcare logistics influenced by ICT advancements. Each part of the study addresses specific issues while collectively offering a unified view of improving efficiency and effectiveness in healthcare logistics.

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