Research On The Home Health Care Routing And Scheduling Problem With Multi-Objective

Home health care routing and scheduling problem(HHCRSP)focuses on the distribution of customer requests and the arrangement of service order paths for home health care nursing.Its purpose is to ensure the customer satisfaction,reduce the cost to the greatest extent,effectively improve the utilization rate of the medical and pension resources,and alleviate the shortage of medical and pension resources.In order to ensure the flexibility and scientificity of routing and scheduling planning,this paper divides the routing and scheduling planning of home health care nursing into two stages: static stage and dynamic stage.In the static planning stage,considering the total cost of service and customer satisfaction,a static home health care nursing routing and scheduling planning model based on multi-objective is established.Then,the key parameters of the basic particle swarm optimization algorithm,which is the model solving method,are determined by the Solomon data set,and the algorithm is improved.The example shows that the improved particle swarm optimization algorithm,the non-linear increasing inertia weight particle swarm optimization algorithm,makes up for the disadvantage that the basic particle swarm optimization algorithm is easy to fall into the local optimal solution,and is more suitable for the static hhcrsp solution.In the dynamic phase,the algorithm will be based on the static hhcrsp model of multi-objective is extended to dynamic hhcrsp model based on multi-objective.Combining the dynamic degree of customer request and the rolling time domain setting principle,different solving strategies are adopted for different dynamic customer requests.The results show that the solution strategy selected in the dynamic phase can effectively reduce the average total cost of customer points and improve customer satisfaction.In order to verify the applicability of the above model,algorithm and strategy,this paper takes the actual data of Qinhuangdao City,Hebei Province,as an example to study the routing and scheduling planning of home health care nursing.The results show that the planning results obtained by the above model and method can still effectively reduce the total cost and improve customer satisfaction,even if the original data set is changed,the best planning can be obtained.This study has theoretical reference value for the expansion of the routing and scheduling planning of home health care nursing and the application of non-linear increasing inertia weight particle swarm optimization algorithm,and it is also conducive to the practical significance of home health care.