SIMULATION–OPTIMIZATION FRAMEWORK FOR HOME-BASED WOUND CARE DELIVERY: ROUTING, SCHEDULING, AND RESOURCE ALLOCATION

Abstract

The increasing demand for decentralized healthcare services has intensified the need for efficient and scalable approaches to manage home-based care delivery. In the context of chronic wound management, patients require frequent and time-sensitive interventions, creating significant operational challenges related to patient triage, resource allocation, routing, and service coordination. This thesis proposes an integrated simulation–optimization framework to support strategic and operational decision-making in home-based wound care systems. The proposed framework combines simulation-based optimization with routing and scheduling optimization to capture both system-level dynamics and operational planning decisions. First, a discrete-event simulation–optimization model is developed to evaluate the interaction between hospital-based and mobile wound care services under uncertainty. The model jointly optimizes staffing levels, fleet size, and AI-supported patient allocation thresholds in order to balance service efficiency, resource utilization, and clinical deterioration risk. Second, the operational routing and scheduling of mobile wound care units is formulated as a Vehicle Routing Problem with Time Windows (VRPTW). To solve the routing problem, three solution approaches are implemented and compared: an exact Mixed Integer Linear Programming (MILP) formulation, Simulated Annealing, and Tabu Search. Computational experiments conducted across benchmark instances of varying sizes demonstrate that the MILP approach provides exact solutions for tractable problem sizes but faces scalability limitations as routing complexity increases. In contrast, the heuristic methods generate high-quality solutions with substantially reduced computational effort, making them more suitable for larger-scale and real-time applications. Among the evaluated heuristics, Simulated Annealing demonstrated the strongest overall performance across benchmark instances. The results highlight the importance of integrating simulation and optimization to support decentralized healthcare planning and demonstrate the value of heuristic routing methods for scalable home-based wound care operations. The proposed framework provides a practical decision-support tool for improving patient allocation, routing, scheduling, and resource planning in decentralized wound care delivery systems.

Date of Award	2026
Original language	American English
Awarding Institution	HBKU College of Science and Engineering