Study On The Public Service Facility Location Problem

Public service facility is the infrastructure of municipal social service, referring to the social foundational facility for educational, medical, cultural and athletic functions for the mass, which is usually spotted in a city. Public service facility location involves fairly allocation of municipal public resources and social fairness. It has become an important feature concerning the living standard of residents and a key issue in city planning and development. Based on the present research, the dissertation aims at public service facility location, extends the covering-model, hierarchical model, Huff gravity model and takes public service facility location under the uncertain circumstances into account. As a real-world case, the public service facility location, such as hospitals, schools, emergency centers based on a district in Wuhan has been discussed. The dissertation can be divided generally into seven parts as follows.Firstly, the background and significance of the study are introduced. The importance of the study lies in planning urban public resources scientifically and reasonably by the reseach of public service facility location, so as to achieve social harmony and improve the quality of life in the city.Secondly, based on the review of previous literatures, the author puts the problem to be studied, which involves covering-model, hierarchical model, Huff gravity model and uncertainty.Thirdly, the dissertation studies the public service facility location problem based on covering model. Conventional location model adopts a set of rigid covering standards, which can't always satisfy the practical needs. A multi-objective public facility location model based on gradual covering is set up, aiming to realize the cost minimization, system effectiveness maximization and to optimize the basic service quality. The evolutionary algorithm is used correspondingly to find solutions based on a district in Wuhan, in which the efficiency of the algorithm has been discussed. In order to slove the problem of facility unavailability when it is busy, a multi-objective public facility location model based on backup coverage is proposed. The objectives in the model are maximization of the population covered by one vehicle, maximization of the population with backup coverage and increasing the service level by minimizing the total travel distance from locations at a distance bigger than a prespecified distance standard for all zones. The Fuzzy Goal Programming (FGP) approach has been used correspondingly to find solutions based on a district in Wuhan and is compared with convitional ones, such as Weighted Linear Method (WLM).Fourthly, the dissertation studies the public service facility location problem based on hierarchical model. For multiple-demand level, facility can be divided into nested and non-nested ones according to the relationship of the facility service levels. For non-nested facility, a public service facility model based on non-nested hierarchical model is set up. As a real-world case, the lagrangian relaxation algorithm has been used to solve the school location-allocation problem of a district in Wuhan, in which three scenarios are discussed: location-allocation rationality at the present, re-location and allocation after fluctuations in demand, and reasonable minimum capacity constrains. For nested facility, a public service facility model based on nested hierarchical model is set up. As a real-world case, the genetic algorithm has been used to solve the hospital location problem based on a district in Wuhan, which includes:the comparation between utility-based and distance-based allocation, the contrast between nested case and non-nested one.Fifthly, the dissertation studies the public service facility location problem based on Huff grivaty model. The author takes different consumption level into account, adopts Huff grivaty model and sets up a consumption-based public facility location model baded on Maximal Coverage Location Model, which aims to realize the maximization of utility of charge facility. As a real-world case, the genectic algorithm has been used to solve the location problem of a district in Wuhan. And the author makes further analysis on the influence of budget constraint, demand and consumption level changes on the optimal solution.Sixthly, the dissertation studies the public service facility location problem under uncertainty. A time-based public service facility location model on efficiency under the uncertain background is set up based on expectancy-value model of stochastic programming and queuing theory. The mixed multi-objective evolutionary algorithm is proposed and the location-allocation is disscused by selecting three approximate Pareto optimal solutions randomly in Pareto optimal front. The changes of average travel time and average stay time are analyzed when the budget and the biggest tolerance time change.Finally, the dissertation summarizes the research and presents a prospect of future study.