A Decision-Making System for Dynamic Scheduling and Routing of Mixed Fleets with Simultaneous Synchronization in Home Health Care

Abstract

Globally, the growing number of elderly people, chronic disorders and the spread of COVID-19 have all contributed to a significant growth of Home Health Care (HHC) services. One of HHC’s main goals is to provide a coordinated set of medical services to individuals in the comfort of their own homes. On the basis of the current demand for HHC services, this paper attempts to develop a novel and effective mathematical model and a suitable decision-making technique for reducing costs associated with HHC service delivery systems. The proposed system of decision making identifies the real needs of HHCs which incorporate dynamic, synchronized services and coordinates routes by a group of caregivers among a mixed fleet of services. Initially, this study models the optimization problem using Mixed Integer Linear Programming (MILP). The Revised Version of the Discrete Firefly Algorithm is designed to address the HHC planning decision-making problem due to its unique properties and its computational complexity. To evaluate the scalability of this proposed approach, random test instances are generated. The results of the experiments revealed that the algorithm performed well even with the different scenarios such as dynamic and synchronized visits. Furthermore, the improved version of nature-inspired solution methodology has proven to be effective and efficient. As a result, the proposed algorithm has significantly reduced costs and time efficiency.