Research on Intelligent Scheduling and Resource Optimization for Elderly Patient Care

Abstract The increasing demographic aging of society has led to the increasing demand for home health care services for the aging population. The planning and scheduling of home care pathways is a challenging problem in in-home medical care services. To this end, this paper proposes an improved hybrid immune genetic algorithm (HIGA) to design a least-cost medical care human resource scheduling strategy for the home care needs of elderly patients so as to provide high-quality home care services for elderly patients. It is tested with a genetic algorithm, modal factorization algorithm and simulated annealing algorithm to compare the arithmetic cases, and then HIGA is applied to find the optimal solution of the path and scheduling planning scheme of home care personnel for elderly patients. In all cases, HIGA has the best optimization effect on the model, and its optimal route cost is lower than the other three algorithms. Its variance is smaller than the other algorithms except for the R121_120 algorithm. This implies that the solutions generated by HIGA are superior and more uniform. The solution time of HIGA is less than 6 seconds in the path and scheduling planning problem of home caregivers for elderly patients in region M. The average total cost of caregivers to serve a single client point is 95, and the proportion of the time window penalty cost to the total cost is only 3.9%, which indicates that it is fast and the quality of its solution is higher, which is in line with the expectations of the decision-makers. This paper is of great significance in designing an effective care resource scheduling method to reduce the operating costs of home care agencies as well as to improve the quality of medical care services for elderly patients.