Improved Artificial Bee Colony Algorithm For City Hospital Layout Research

The hospital,as an important part of urban public facilities,is directly related to the future development of cities and the happiness index of urban residents.Reasonable urban hospital layout can not only meet the needs of urban economic development,but also meet the requirements of urban residents for healthy and better life.Therefore,how to mitigate the effects of migration on urban hospital layout to the maximum extent,and effectively improve fairness,economy and efficiency of the city hospital layout are particularly important.Based on this,the dissertation proposes an improved artificial bee colony algorithm to solve the problem of urban hospital layout.Firstly,the dissertation describes the research background of urban hospital layout problems and emphasizes the research value and necessity of the problem.At the same time,the basic conditions and influencing factors of urban hospital layout are elaborated,and the basic principles of fairness,economy and efficiency are applied to the layout of urban hospitals.When studying the layout of urban hospitals,the principle of fairness,economy and efficiency should be considered.When considering the fairness of the layout,the study area should be divided into administrative region and the gravity accessibility model can be constructed.By calculating the number of hospital beds in the region,the number of hospitals is ensured in the region,and the economy of hospital construction can be guaranteed under the premise of meeting the healthy demand of urban residents.In order to improve the efficiency of the urban residents' medical treatment,the shortest total distance should be ensured.Meanwhile,the multi-objective mathematical model of urban hospital layout is constructed based on the preference psychology and urban traffic condition of urban residents.Secondly,the artificial bee colony algorithm is regarded as the main theoretical research method,through understanding the basic principle and basic process of algorithm,the internal operation mechanism of the algorithm is learned,and a targeted improvement is done for the algorithm after the shortcomings of the algorithm are found,the multiobjective artificial swarm algorithm is proposed combining multi-objective optimization theory with artificial bee colony algorithm.Because basic multi-objective artificial bee colony algorithm exists shortcomings,such as population blind search,limited algorithm development ability and so on.Reverse learning strategy,mutation mechanism and adaptive search mechanism are introduced to algorithm of the dissertation,which will make the individual species be targeted for updates and improve the diversity of population individuals greatly.The analysis of the test function shows that the improved algorithm can effectively improve the convergence and reconciliation of the algorithm.Finally,taking Ma Anshan urban hospital layout as an example,to design algorithm program and simulate for mathematical model is done by using the improved multi-objective artificial bee colony algorithm combining with the urban hospital layout mathematical model,and the Pareto optimal solution set is found out,the dissertation introduces the method of grey correlation degree,through grey correlation analysis for each Pareto optimal solution,the optimal solution is chosen easily from the optimal solution set,which is the optimal layout scheme of city hospital,it provides theoretical guidance for the construction of urban hospitals and rational allocation of resources.