| To face the situation of aging population in China,establishing and promoting a Home Health Care system can increase the medical supply,and meet the diversified and differentiated medical and care needs of the elderly.Home Health Care services supply are still insufficient and unbalanced in China,and the elderly nursing manpower are particularly scarce.Therefore,it is important to reasonably arrange the existing nursing personnel to make full use of the service capabilities.At present,the manpower scheduling and routing in Home Health Care is mostly based on the assumption of one center or one region.The scheduling and routing plans lack cross-centers or cross-regions coordination.The results could be local optimal rather than global optimal.Thus,this research takes the cross-regions manpower scheduling and routing problem into account.This study proposes a cross-regions scheduling and routing model,considering objectives that affect care center costs,patient satisfaction,and nursing personnel satisfaction.A range of possible realistic constraints are considered,such as patient time windows,working regulations,task importance,and skill matching.To solve the model,this study proposes a hybrid Simulated Annealing algorithm framework,in which the memory structure of the Tabu Search algorithm is introduced.Also,this research uses the Monte Carlo simulation method for the uncertainty cost evaluation.The numerical example tests verify the effectiveness of the algorithm proposed in this study.By comparing the empirical experiment results of the cross-regions and independent scheduling of two regions,this study analyzes the advantages and disadvantages of the cross-regions scheduling and routing.It is found that in the case of this study,cross-regions scheduling is generally beneficial to reduce the cost of both care centers and improve the efficiency of resource utilization.At last,through the sensitivity analysis of patient time windows and the nursing personnel’s skill level,some operations management suggestions for stakeholders are commented based on the empirical results. |