Research On Scheduling Model Based On Collaborative Cognition Of Pharmaceutical Service Resources

With the in-depth integration of information technologies such as mobile Internet of Things,cloud computing,big data,and 5G with the pharmaceutical industry,the rise of the "Internet + health" model has accelerated the development process of the pharmaceutical industry,and pharmaceutical services have quickly become a research hotspot in academic and industry community.Aiming at the problems of increasing pharmaceutical service resources,fragmentation of service resources,poor service quality,and poor user experience,this thesis focuses on the scenario of pharmaceutical services,establishes a collaborative cognitive scheduling association model for pharmaceutical service resources to realize the optimal scheduling of pharmaceutical service resources among pharmaceutical companies,hospitals and patients.This thesis mainly studies the bilateral stable matching method of the collaborative cognition of pharmaceutical service resources between pharmaceutical companies and hospitals,and the combined optimization method of the collaborative cognition of pharmaceutical service resources between hospitals and patients to realize the stable operation of the pharmaceutical industry chain and meet the urgent needs of patient pharmaceutical service customization.The specific research content is as follows:(1)An association model for collaborative cognition of pharmaceutical service resources is established.Based on different subjects,it integrates the pharmaceutical service resources involved in the three parts of pharmaceutical companies,hospitals and patients,and clarifies the synergy of pharmaceutical service resources among pharmaceutical companies,hospitals and patients.The pharmaceutical service resources are clustered based on the similarity of their resource attributes to establish the association between the pharmaceutical service and resources.Through the similarity clustering and correlation distribution of the pharmaceutical service resource attributes,the association model of the collaborative cognition of pharmaceutical service resources is constructed,which lays the foundation for solving the problem of bilateral stable matching and combination optimization of pharmaceutical service resources.(2)A method of bilateral stable matching of pharmaceutical service resources is proposed.Aiming at the bilateral stable matching of pharmaceutical service resources between pharmaceutical companies and hospitals,a preference order value list for pharmaceutical companies to hospitals based on relative distance and a preference order value list for hospitals to pharmaceutical companies based on Pharmaceutical Quality of Service(QoS)are constructed respectively.At the same time,a bilateral stable matching model between pharmaceutical companies and hospitals based on the preference order value list is constructed.In terms of stability and repeatability,experiments of the Gale-Shapley algorithm have proved that the cycle times and repeated markings of bilateral stable matching of pharmaceutical service resources have been effectively improved.(3)A method to optimize the collaborative combination of pharmaceutical service resources is proposed.Aiming at the optimization problem of the combination of hospital and patient pharmaceutical service resources,this thesis analyzes the QoS attributes of hospital pharmaceutical service resources,and constructs a QoS model of pharmaceutical service resources based on Markov decision process.By comparing and analyzing the traditional single-step Q-learning algorithm and the improved Q-learning algorithm,it is proved that the operational efficiency of the pharmaceutical service resources,the pharmaceutical service resource combination success rate and the total reward value of the optimization target based on the improved Q-learning algorithm have been significantly improved.