Genetic algorithm enhanced by levy flight for dynamic vehicle routing problem with time window in home healthcare

Abstract

In the present modern Healthcare system, demands for Home Healthcare services have drastically increased, especially during pandemic outbreaks such as the covid-19 infections. Home Healthcare (HHC) system is meant to provide a flexible method of healthcare services at the patient's home. Since HHC has limited and multi-dimensional resources, its demand is extensively high. As a result, the allocation of resources is one of the most complex and critical tasks for the HHC operational team. The inclusion of dynamic resources in their scheduling and routing plans becomes even more challenging for the HHC team. Hence, we investigate the Dynamic Vehicle routing problem with time window (DVRPTW) using the constraints for adding new patients to the existing route plan based on their preferred timeslots. In order to solve this combinatorial problem, we used Genetic Algorithm (GA) enhanced by Levy Flight (LF) to minimize total travel and idle time and maximize new patient visits in every route plan. In this paper, we evaluated the efficiency of the proposed algorithm by comparing it to the well-known Nearest Neighborhood algorithm, and found that it outperforms well. Thus, by adopting GA along with LF in the HHC organizations can benefit from cost effective and time saving solutions.