Research On Integrated Multi-Resource Collaborative Optimization Problems For Operating Rooms

At present,the total amount of high-quality medical resources in China is in shortage,the development of various regions is unbalanced,and the contradiction between supply and demand of medical services still exists.Most patients prefer large public hospitals.The overall utilization rate of service resources of medical institutions at all levels is low.The operating room,as the most intensive department of medical resources,carries the most critical medical links.However,the diversity of medical resources and the multimodal characteristics of the main body of emergency medical cooperation bring challenges to the reasonable and unified operation room resources collaborative optimization.In addition,the increasingly subdivided types of surgeries,cumbersome surgical procedures,and uncertain surgery time and other complex and dynamic needs make it difficult to give consideration to service quality and service efficiency for operating room multi-resource optimization.In view of this,for the hospitalized elective patients and non-elective patients admitted in emergency,we carries out the research of multi-resource integration and collaborative optimization in the operating room under routine situation and large-scale casualties respectively,so as to improve the efficiency of operating room resource utilization and improve the quality of hospital service.In this dissertation,the problem characteristics,decision-making levels,scheduling strategies,optimization models and solution methods of operating room resource scheduling research at home and abroad are sorted out and analyzed,and the multi-stage problems and multi-hospital operating room resource joint scheduling problems that are difficult to solve in existing research are summarized.Three stage operating room scheduling model,fixed transportation route operating room scheduling model and nonfixed transportation route operating room scheduling model are established,respectively.The structural properties of the scheduling problem are analyzed,and effective heuristic algorithms are constructed.Since the problems are NP-hard,a variety of hybrid meta heuristic algorithms are proposed,and the effectiveness and superiority of the algorithm are verified by a large number of experiments.The specific research contents and main innovative work are as follows:(1)The dynamic three-stage operating room collaborative optimization problem for elective patients in the regular situation is studied.We propose a mixed integer programming mathematical model,which aims to minimize the waiting cost of patients and the operating room overtime cost.To solve the problem,some structural characteristics are proposed,and two constructive heuristic algorithms are proposed based on these structural characteristics.We prove that the studied operating room scheduling problem is NP hard,and design a hybrid grey wolf optimization-variable neighborhood search algorithm(GWO-VNS).Finally,we test the efficiency,stability and convergence speed of the proposed algorithm through simulation experiments,and compare it with other competitive algorithms.(2)The collaborative scheduling problem of multi-hospital operating rooms with fixed transportation routes for non-elective patients is studied.We propose a mixed integer programming model,considering the deterioration of patients’ health condition and ambulance offload delay.The goal is to minimize the maximum surgery completion time.Due to the complexity of the problem,we derive some structural properties of the problem and propose a structural heuristic algorithm.We propose a hybrid firefly-variable neighborhood search algorithm(FA-VNS).Through a series of simulation experiments,we test the performance of FA-VNS and compare it with other three meta-heuristic algorithms.The results show the effectiveness and superiority of the proposed algorithm.(3)The collaborative operating room scheduling problem of multiple hospitals with non-fixed transportation routes for non-elective patients is studied.We establish a mixed integer programming model of joint ambulance scheduling and multi-hospital operating room scheduling in mass casualty incidents.We make collaborative decisions on patients to multi-hospital operating room allocation and operation sequencing scheme,with the goal of maximizing the number of patients undergoing surgery before the optimal clinical treatment time.Since the studied problem is NP-hard,we develop a hybrid tabu searchadaptive large neighborhood search algorithm(TS-ALNS).There are three new customized removal operators.We use the exact solver Gurobi to solve the model,and compare the results of small-scale instances obtained by the hybrid algorithm to verify the effectiveness of the model.Large-scale experiments are also carried out to demonstrate the superiority of the proposed algorithm compared with other similar algorithms and the necessity of the customized removal operators.In this dissertation,the multi-resource collaborative optimization problem of operating room is studied systematically.By considering the characteristics of surgeries’ risk level,patients’ health deterioration and ambulance offload delay,three-stage operating room scheduling model,fixed transportation route operating room scheduling model and non-fixed transportation route operating room scheduling model are established.On this basis,the structural properties of the problem are derived,and the hybrid grey wolf-variable neighborhood search algorithm,hybrid firefly-variable neighborhood search algorithm and hybrid tabu search-adaptive large neighborhood search algorithm are designed respectively to solve the problems.It is worth noting that there are still many problems to be further studied and explored in the future.How to consider the simultaneous scheduling of elective patients and non-elective patients,how to consider the multi-objective operating room multi-resource collaborative optimization from the perspective of hospital and medical staff,and to consider the uncertainty of more factors related to the operation tasks in combination with the actual situation,so as to design a more practical and easy-to-use efficient algorithms is an important research direction in the future.