Home Health Care Scheduling Problem In The Gig Economy

Since the 21 st century,a series of developed countries and developing countries,including China,are facing the problem that the proportion of the elderly population is increasing year by year,and the increasingly severe population aging trend has put great pressure on national medical care system.One of the major problems faced by the government of China is to reasonably allocate the existing medical resources to serve the elderly in need of medical services.Home Health Care(HHC)service is a new service mode nursing for older adults that has emerged in recent years.HHC services take hospitals,community nursing homes and social enterprises that provide medical services as the main body,and through these institutions,caregivers are assigned to provide a variety of nursing services to help patients recover from injury or illness in their homes.In recent years the service mode of the gig economy has emerged in many service industries with the development of Internet technology.To decrease fixed labor costs and increase the use of human resources,some HHC companies have established their gig-economy platform to provide online appointments for medical services.In this context,one of the greatest challenges for HHC providers is to assign the labor resource to optimize company’s operating costs.This thesis aims to provide an optimized decision-making scheme for HHC scheduling problems in the gig economy,and the main research contents include the following four parts:(1)In the literature review,the concept of home health care routing and scheduling problem is firstly introduced,the research papers in the field in recent years are classified according to constraints and optimization objectives;next,the literature on home health care routing and scheduling problem with uncertainties is investigated;then,the difficulty of solving bi-level programming is explained,and we investigate the related literature using bi-level programming to solve routing problems at the same time.Finally,a brief summary for the literature review is given,and the contributions of this thesis is illustrated.(2)The background of the HHC scheduling problem under the gig economy is introduced and a bi-level programming model for home health care routing and scheduling problem(BHHCRSP)is established,in which the upper level represents the HHC company’s assignment decision and the lower level represents the caregivers’ routing and time scheduling decision.(3)A two-stage exact algorithm and a hybrid meta-heuristic approach are designed for solving the proposed BHHCRSP.The developed exact algorithm includes two stages: in the first stage,all feasible routes of the lower-level problem are generated by an implicit enumeration algorithm based on constraint checking;in the second stage,a set-partition(SP)formulation is built to find the optimal solution of the bi-level model from all the generated routes.The developed hybrid meta-heuristic approach is composed of an iterated local search meta-heuristic,which uses a large neighborhood search as a sub-heuristic in the local search phase,and an SP formulation.In the first stage of the algorithm,the iterated local search iteratively fills the pool with the routes in every local optimal solution;in the second stage,an SP formulation is built by using the pool of routes,and then the formulation is iteratively solved.Numerical experiments on a set of instances verify the effectiveness of the proposed model and algorithms.(4)The BHHCRSP is further extended from the perspective of considering the stochastic environment,and a stochastic bi-level programming model for home health care routing and scheduling problem is proposed.By analyzing the characteristics of the stochastic model,a three-stage hybrid algorithm is developed to solve the problem.A series of experiments are performed to analyze the characteristics of the stochastic model and to verify the effectiveness of the proposed algorithm.