Designing the home healthcare supply chain during a health crisis

TLDR

During the COVID‑19 pandemic, home‑healthcare supply chain actors highlighted the importance of home care services, with pharmacies positioned near patients and nurses routed according to patient needs. This study proposes and solves an integrated location‑allocation‑routing model for the home‑healthcare supply chain, emphasizing the use of the LP‑metric method. The authors implement LP‑metric and epsilon‑constraint methods to solve the model, comparing objective function values and computational times. The LP‑metric method achieves lower mean ideal distance, higher simultaneous objective achievement, and faster computation, and TOPSIS analysis confirms the model’s efficiency for home‑healthcare supply chain companies during COVID‑19.

Abstract

During the COVID-19 pandemic, sectoral contributors to home healthcare supply chain (HHCSC) corporations highlighted the role of home care services. Pharmacies are located where patients are allocated to them, and nurses are routed and scheduled according to their patients' needs. It is the first study to propose an integrated location-allocation-routing model, which includes all preliminaries necessary to make these decisions. We implement the LP-metric and epsilon-constraint methods to solve this model, and then we discuss the results of these methods. A comparison is also made regarding the objective function values and the time taken to solve the problem. The average, mean ideal distance (MID) (3.74;3.19), the rate of achievement of two objectives simultaneously (RAS) (1.71;3.56), and computational time (CPU time) (1.92;24.92) for two ɛ-constraint and LP-Metric methods is calculated. The superior technique is finally selected by utilizing the TOPSIS. To solve the study's mathematical model, the LP-metric method is worth implementing. Based on these results, the suggested model for HHCSC companies, and employees' performance, is efficient during the COVID-19 pandemic.