| Preventive health services can prevent diseases through a series of health services,so that residents can maintain physical and mental health.With the gradual improvement of people’s awareness of disease prevention,the medical concept of “seeing a doctor if you are sick,and health care without diseases” is gradually taking shape.Therefore,residents’ demand for preventive medical care is also increasing,and the network layout of preventive health services is proposed High demands.At present,my country’s community preventive health service network has problems such as uneven resource allocation,low service levels,unreasonable medical staffing,and failure to consider service station congestion and long-term changes in demand.The high construction cost and long service life of preventive healthcare services have a profound impact on site selection and capacity allocation decisions.The traditional preventive health service network optimization model assumes that all parameters are determined,but in actual operation,service station congestion and long-term demand changes will cause the traditional community preventive health service network optimization model to no longer apply.In view of the above background,it is necessary to consider the optimization of the community preventive health service network under the uncertain demand.This article takes the preventive health service network in a specific area as the object.In the process of optimizing the design of the community preventive health service network,on the one hand,the demanders require that the time to the preventive health service station be shortened,and the waiting time before receiving the service is less;On the other hand,preventive health service providers need to reduce costs while providing high-quality and timely services.This paper establishes a dual-objective model with the smallest travel distance of the preventive health service demanders and the smallest total system cost,and analyzes the uncertain factors in the site selection and capacity allocation of preventive health services.To this end,based on the existing community health service center as a candidate site for preventive health service stations,combined with the characteristics of preventive health services,comprehensive consideration of uncertain factors such as service station congestion and long-term population changes.Queuing theory is used to consider service station congestion and service time fluctuations,and to measure service levels,and then use the nature of service level constraints to transform the nonlinear model into a linear model.In addition,robust optimization is used to capture long-term demographic changes,a basis-constrained robust optimization method is used to deal with uncertain demand parameters,and a robust corresponding model is proposed.This paper establishes a robust optimization model for the community preventive health service network by considering uncertain factors such as service station congestion and long-term population growth,which can realize the scientific location of preventive health service stations and the reasonable allocation of capacity,and allocate appropriate preventive health services to those who need them.Service site.In this paper,the NSGA-II algorithm is designed to solve the dual-objective robust optimization model and the effectiveness and robustness of the model are verified through the analysis of examples.Based on the empirical analysis of the chronic disease prevention and health care service network in Luohu District,Shenzhen,based on the robust optimization model designed in this paper,the chronic disease prevention and health care services in Luohu District,Shenzhen were re-arranged and optimized,and the population growth rate was calculated.As well as the sensitivity analysis of the service rate,it proves the importance of considering the robustness of the preventive healthcare service network solution in maintaining the required service level. |
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