公共服务设施选址问题研究
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摘要
公共服务设施是城市社会性服务业的依托载体,是指城市中呈点状分布并服务于社会大众的教育、医疗、文体等社会性基础设施。公共服务设施选址问题事关城市公共资源的公平分配和社会公正,是反映居民生活质量的重要标志,也是城市规划和城市发展的中心议题。在现有研究的基础上,论文围绕公共服务设施选址问题,对覆盖模型、层次模型及重力模型进行了拓展,并考虑了不确定性条件下的选址问题,以武汉市某区医院、学校、急救中心等公共服务设施选址为例进行研究。本论文的研究总体上分为七个部分：
第一,论文介绍了研究背景和意义,本论文研究的目的和意义在于,通过对公共服务设施选址问题的探讨,达到城市公共资源的科学合理配置,从而实现社会和谐,提高城市居民生活质量。
第二,在对国内外文献进行分析、总结的基础上,分别从覆盖模型、层次模型、重力模型、不确定性四个方面提出了要研究的问题。
第三,论文对基于覆盖模型的公共服务设施选址问题进行了研究。针对传统的选址问题设置严格覆盖半径这一不切合实际的情况,论文引入渐进覆盖的概念,以成本最小化、系统效用最大化及基本服务质量最大化为目标,建立了基于渐进覆盖的多目标公共服务设施选址模型,设计了相应的进化算法进行求解,并以武汉市某区小学选址为例进行了案例研究,且就算法的有效性进行了讨论。针对公共服务设施处在工作状态,需求区域看似被覆盖而实际上出现服务设施不可达的现象,论文引入备用覆盖的概念,以一次覆盖人口最大化、至少两次覆盖的人口最大化以及在选址点与需求点超过覆盖距离的情况下,系统总的旅行距离之和最小化为目标,建立了基于备用覆盖的多目标公共服务设施选址模型,以武汉市某区急救中心选址为例进行案例分析,用模糊目标规划方法进行求解,并与传统的多目标求解方法——线性加权法进行比较。
第四,论文对基于层次模型的公共服务设施选址问题进行了研究。对于多层需求而言,根据设施各层级提供服务水平的相互关系可分为嵌套型与非嵌套型。对于非嵌套型而言,论文提出基于非嵌套的层次模型的公共服务设施选址模型,使用拉格朗日松弛算法,以武汉市某区学校选址为例,就目前选址及分配的合理性问题、需求波动后的重新选址及分配问题和学校最小容量的合理设置问题进行了分析。对于嵌套型而言,论文提出基于嵌套的层次模型的公共服务设施选址模型,利用遗传算法,以武汉市某区医院选址问题为例进行案例分析,并就按效用分配与按距离分配的情况进行对比分析,就嵌套情况与非嵌套情况进行比较与讨论。
第五,论文对基于重力模型的公共服务设施选址问题进行了研究。论文首先考虑客户不同的消费水平,引入Huff重力模型,以收费设施的效用最大化为目标,在最大覆盖选址模型基础上建立基于重力模型的公共服务设施选址模型,使用遗传算法进行求解,以武汉市某区小学选址为例进行案例研究,并进一步分析了预算约束、需求及消费水平变化对于最优解的影响。
第六,论文对不确定性的公共服务设施选址问题进行了研究。利用随机规划的期望值模型,引入排队论,建立了需求不确定条件下基于时间效率的公共服务设施选址模型,通过混合多目标进化算法进行求解,并随机选取Pareto优化前沿3个近似Pareto最优解,对其选址及分配情况进行分析,还就预算及最大容忍时间发生变化时平均旅行时间和平均逗留时间变化情况进行分析。
最后,对全文进行全面总结,并对将来进一步有待深入研究的工作作了展望。
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.
第一,论文介绍了研究背景和意义,本论文研究的目的和意义在于,通过对公共服务设施选址问题的探讨,达到城市公共资源的科学合理配置,从而实现社会和谐,提高城市居民生活质量。
第二,在对国内外文献进行分析、总结的基础上,分别从覆盖模型、层次模型、重力模型、不确定性四个方面提出了要研究的问题。
第三,论文对基于覆盖模型的公共服务设施选址问题进行了研究。针对传统的选址问题设置严格覆盖半径这一不切合实际的情况,论文引入渐进覆盖的概念,以成本最小化、系统效用最大化及基本服务质量最大化为目标,建立了基于渐进覆盖的多目标公共服务设施选址模型,设计了相应的进化算法进行求解,并以武汉市某区小学选址为例进行了案例研究,且就算法的有效性进行了讨论。针对公共服务设施处在工作状态,需求区域看似被覆盖而实际上出现服务设施不可达的现象,论文引入备用覆盖的概念,以一次覆盖人口最大化、至少两次覆盖的人口最大化以及在选址点与需求点超过覆盖距离的情况下,系统总的旅行距离之和最小化为目标,建立了基于备用覆盖的多目标公共服务设施选址模型,以武汉市某区急救中心选址为例进行案例分析,用模糊目标规划方法进行求解,并与传统的多目标求解方法——线性加权法进行比较。
第四,论文对基于层次模型的公共服务设施选址问题进行了研究。对于多层需求而言,根据设施各层级提供服务水平的相互关系可分为嵌套型与非嵌套型。对于非嵌套型而言,论文提出基于非嵌套的层次模型的公共服务设施选址模型,使用拉格朗日松弛算法,以武汉市某区学校选址为例,就目前选址及分配的合理性问题、需求波动后的重新选址及分配问题和学校最小容量的合理设置问题进行了分析。对于嵌套型而言,论文提出基于嵌套的层次模型的公共服务设施选址模型,利用遗传算法,以武汉市某区医院选址问题为例进行案例分析,并就按效用分配与按距离分配的情况进行对比分析,就嵌套情况与非嵌套情况进行比较与讨论。
第五,论文对基于重力模型的公共服务设施选址问题进行了研究。论文首先考虑客户不同的消费水平,引入Huff重力模型,以收费设施的效用最大化为目标,在最大覆盖选址模型基础上建立基于重力模型的公共服务设施选址模型,使用遗传算法进行求解,以武汉市某区小学选址为例进行案例研究,并进一步分析了预算约束、需求及消费水平变化对于最优解的影响。
第六,论文对不确定性的公共服务设施选址问题进行了研究。利用随机规划的期望值模型,引入排队论,建立了需求不确定条件下基于时间效率的公共服务设施选址模型,通过混合多目标进化算法进行求解,并随机选取Pareto优化前沿3个近似Pareto最优解,对其选址及分配情况进行分析,还就预算及最大容忍时间发生变化时平均旅行时间和平均逗留时间变化情况进行分析。
最后,对全文进行全面总结,并对将来进一步有待深入研究的工作作了展望。
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.
引文
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