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1.
Allocation for earthquake emergency shelters is a complicated geographic optimization problem because it involves multiple sites, strict constraints, and discrete feasible domain. Huge solution space makes the problem computationally intractable. Traditional brute-force methods can obtain exact optimal solutions. However, it is not sophisticated enough to solve the complex optimization problem with reasonable time especially in high-dimensional solution space. Artificial intelligent algorithms hold the promise of improving the effectiveness of location search. This article proposes a modified particle swarm optimization (PSO) algorithm to deal with the allocation problem of earthquake emergency shelter. A new discrete PSO and the feasibility-based rule are incorporated according to the discrete solution space and strict constraints. In addition, for enhancing search capability, simulated annealing (SA) algorithm is employed to escape from local optima. The modified algorithm has been applied to the allocation of earthquake emergency shelters in the Zhuguang Block of Guangzhou City, China. The experiments have shown that the algorithm can identify the number and locations of emergency shelters. The modified PSO algorithm shows a better performance than other hybrid algorithms presented in the article, and is an effective approach for the allocation problem of earthquake emergency shelters.  相似文献   

2.
The spatial allocation of water resources is optimised using the multi-objective functions and multi-constrained conditions of the Pareto ant colony algorithm (PACA). The objective function is the highest benefit to the economy, society and the environment, while the constraints include water supply, demand and quality. The PACA is improved by limiting local pheromone scope and dynamically updating global pheromone levels. Since both strategies guide the ant towards borders of high-pheromone concentration, the new approach enhances the global search capability and convergence speed. Programming, database management and interface tools are then integrated into geographic information systems (GIS) software. The study area is located in Zhenping County, Henan Province, China, and water resource data are obtained using remote sensing (RS) and GIS technology. The improved PACA is solved in the GIS environment. Optimal spatial allocation schemes are obtained for surface, ground and transferred water and the model yields optimal spatial benefit schemes of water resources, embracing economic, social and ecological benefits. The results of improved PACA are superior to those of other intelligent optimisation algorithms, including the ant colony algorithm, multi-objective genetic algorithm and back-propagation artificial neural network. Therefore, the integration of RS, GIS and PACA can effectively optimise the large-scale, multi-objective allocation of water resources. The model also enhances the global search capability, convergence speed and result precision, and can potentially solve other optimal spatial problems with multi-objective functions.  相似文献   

3.
Optimizing land use allocation is a challenging task, as it involves multiple stakeholders with conflicting objectives. In addition, the solution space of the optimization grows exponentially as the size of the region and the resolution increase. This article presents a new ant colony optimization algorithm by incorporating multiple types of ants for solving complex multiple land use allocation problems. A spatial exchange mechanism is used to deal with competition between different types of land use allocation. This multi-type ant colony optimization optimal multiple land allocation (MACO-MLA) model was successfully applied to a case study in Panyu, Guangdong, China, a large region with an area of 1,454,285 cells. The proposed model took only about 25 minutes to find near-optimal solution in terms of overall suitability, compactness, and cost. Comparison indicates that MACO-MLA can yield better performances than the simulated annealing (SA) and the genetic algorithm (GA) methods. It is found that MACO-MLA has an improvement of the total utility value over SA and GA methods by 4.5% and 1.3%, respectively. The computation time of this proposed model amounts to only 2.6% and 12.3%, respectively, of that of the SA and GA methods. The experiments have demonstrated that the proposed model was an efficient and effective optimization technique for generating optimal land use patterns.  相似文献   

4.
区位—分配模型是实现公共服务设施最适配置的有效方法之一。传统的P中值模型以效率作为导向,采用“邻近分配”规则,不考虑设施容量(规模),难以适应城市综合医院供需之间相互作用规律下适度均衡、居民随机概率式选择和区位与规模同步求解的布局要求。本文尝试以P中值模型为基础框架,在对P中值模型来源及其适用性进行分析的基础上,构建出基于供需双方(居民—综合医院)空间相互作用的重力P中值模型。新模型通过纳入“邻近就医”最大出行成本因子,确保居民至少邻近1所综合医院(保障空间公平);通过追求总加权出行成本最小化,确保设施空间配置效率;通过纳入设施容量规模因子实现设施区位和规模同时求解;通过纳入最小规模因子,保障设施规模效率和服务质量公平。进一步通过无锡市区综合医院空间配置进行实证检验发现：采用新模型优化后,综合医院空间配置更加公平、居民邻近就医更加便捷,且能够实现与社区卫生设施协同布局,使整个医疗设施体系空间布局更加合理。本文构建的新重力P中值模型(模型的变量参数可作适当调整)可用于竞争型公共设施区位决策,为相关设施布局调整或者规划提供决策依据。  相似文献   

5.
田玲玲  张晋  王法辉  李响  郑文升  罗静 《地理科学》2019,39(9):1455-1463
公共服务资源的空间配置问题一直存在效率与公平价值导向的博弈,空间综合人文社科的兴起,使其演化成一个空间优化问题。医疗资源空间配置的规划注重决策连续性,据此提出改进空间可达性的两步优化法。在农村地区资源有限的情况下,以空间可达性为主要指标,建立公平与效率导向下的二次规划模型,通过重新选址和设定规模以保证居民获得就医机会的最大公平和效率,并以湖北省仙桃市为案例进行应用研究。结果表明,新选地址和规模优化结果能使仙桃市医疗资源空间配置的公平性和效率性得到显著提高,2个步骤相结合,使其成为真正的混合优化模型,达到效率和公平平衡的双重目标。  相似文献   

6.
Location siting is an important part of service provision, with much potential to impact operational efficiency, safety, security, system reliability, etc. A class of location models seeks to optimize coverage of demand for service that is continuously distributed across space. Decision-making and planning contexts include police/fire resource allocation for a community, siting cellular towers to support cell phone signal transmission, locating emergency warning sirens to alert the public of severe weather and other related dangers, and many others as well. When facilities can be sited anywhere in continuous space to provide coverage to an entire region, this is a very computationally challenging problem to solve because potential demand for service is everywhere and there are an infinite number of potential facility sites to consider. This article develops a new parallel solution approach for this location coverage optimization problem through an iterative bounding scheme on multi-core architectures. The developed approach is applied to site emergency warning sirens in Dublin, Ohio, and fire stations in Elk Grove, California. Results demonstrate the effectiveness and efficiency of the proposed approach, enabling real-time analysis and planning. This work illustrates that the integration of cyberinfrastructure can significantly improve computational efficiency in solving challenging spatial optimization problems, fitting the themes of this special issue: cyberinfrastructure, GIS, and spatial optimization.  相似文献   

7.
基于多目标遗传算法的土地利用空间结构优化配置   总被引：12，自引：0，他引：12  
针对如何将土地利用数量结构落实到具体的地域空间，以实现土地资源的优化配置的土地利用总体规划编制难点，以及常规的叠加法等土地利用配置方法难以根据土地适宜性评价结果，有效地将土地利用数量结构匹配到具体的土地单元问题，该文利用遗传算法的内在并行机制及其全局优化的特性，提出了基于多目标遗传算法的土地利用空间结构优化配置方法。实例分析表明，该方法具有客观性强、灵活性高、操作简便等优点。  相似文献   

8.
公平导向的学校分配空间优化——以北京石景山区为例   总被引：6，自引：0，他引：6  
戴特奇  廖聪  胡科  张文新  刘正兵 《地理学报》2017,72(8):1476-1485
空间优化正从地理学的一个研究方向成为学科分支,但公平导向的公共服务空间分配优化研究还较薄弱。学区配置是这方面的一个典型问题,受到社会的广泛关注。针对“多校划片”的随机入学方式,以各居住小区所获得的教育质量期望值的方差来定义入学指标空间分配的公平程度,构建了以该方差最小化为目标、包含最大上学距离约束的二次规划模型,探求各小区对所获得指标进行随机抽签的情景下,各校入学指标在各小区的公平最大化分配,并以北京市石景山区为案例进行了应用研究。结果表明,在维持学校布局和师资配置现状的前提下,与“就近入学”相比,公平最大化的“多校划片”能以有限的上学距离代价,显著降低教育分配的空间差异。在最大上学距离为5 km的约束下,各小区教育质量期望值的方差降幅高达99%,教育质量期望值有所提升的小区或学生比例高达约2/3;付出的上学距离代价较显著但可接受,平均上学距离增加到3.99倍,达到3.20 km,仍低于案例区实际平均上学距离。当模型的最大上学距离参数从5 km逐步增至8 km时,教育公平的改善呈指数增长,平均上学距离呈算数增长;当距离为7 km时,各小区教育质量期望值的方差趋近于0,可基本实现上学机会的空间均等化。本文进一步讨论了优化结果对入学政策的启示。  相似文献   

9.
基于资源效率的国土空间布局及支撑体系框架   总被引：5，自引：0，他引：5  
形成国土空间开发保护新格局是生态文明建设的首要任务之一,关键在于城镇、农业和生态空间的合理配置,重点是以较小的资源损耗支撑社会经济可持续发展,而深入理解资源效率的作用成效是科学优化国土空间布局的前提。本文框架以城镇利用、农业生产和生态转换效率测算为逻辑起点,构建以上述效率为核心的国土空间开发保护情景方案和评价指标体系,引入体现决策偏好差异模型评价国土空间发展潜力,定量刻画不同情景方案下的国土空间布局蓝图,最后通过综合性分析范式对不同决策导向的国土空间政策工具（布局蓝图）进行模拟和优选。本文通过揭示资源效率对国土空间开发保护的作用成效,提炼国土空间布局蓝图定量刻画的具体规律,构建权衡多方利弊的全局优化策略,为国家生态文明建设和自然资源统筹管理提供理论参考。  相似文献   

10.
We developed a new approach combining statistical and graphical methods to build a hierarchically networked structure for understanding spatial characteristics of urban landscapes at multiple scales. Natural breaks optimization algorithm is applied to determine the optimal number of urban land hierarchies and assign discrete patches into ordered sub-groups according to a selected geometric or functional attribute. Patches contained in a sub-group are linked to the patches in the next sub-group according to the spatial relationships between the patch centroids and Voronoi cells. The conceptual foundations and technical details of this approach are elaborated in the case study of building a hierarchically networked structure of urban built-up patches in Beijing. This approach can be applied to quantify landscape patterns of other land uses to facilitate assessments of interconnection between various types of land uses at varied hierarchical levels (spatial scales) and to evaluate ecological service functions of urban built infrastructures.  相似文献   

11.
A new approach for treating multi-objective spatial optimization problems is introduced in this study, aiming at deriving the optimal spatial allocation of Wind Farms on a Greek Island (Lesvos). This work builds on the knowledge gained from numerous applications of multi-objective genetic algorithms, either for spatial planning purposes or for other engineering-related topics, by incorporating modified genetic operators and sophisticated planning criteria. Hence, a stand-alone genetic optimizer was developed that incorporates the controlled non-dominated sorting genetic algorithm-II (CNSGA-II), in which the user can model all planning criteria and constraints for every spatial entity to be allocated, and handle the genetic solver via a built-in computational framework that permits the analysis of large terrains. The presented paradigm provides interesting findings for the optimal development of renewable energy sources projects whose spatial allocation is governed by conflicting criteria and strict constraints.  相似文献   

12.
学校分区问题混合元启发算法研究   总被引：5，自引：0，他引：5  
中国城市义务教育学校采用单校划片或多校划片的方式确定招生范围,落实就近入学的法律要求。针对多校划片这一新的学校分区问题,提出“先学校分组,再学生分派”的策略进行划片,并设计了学校分组线性规划模型和学校分区混合元启发算法。分区算法包括初始解构造、邻域搜索算子、破坏重建扰动、集合划分问题（SPP）建模与求解等基本模块,在多启动迭代局部搜索（ILS）算法框架中进行问题求解。通过多启动、随机搜索、破坏重建扰动等机制提升算法的多样性,并引入SPP模型提升算法的全局寻优能力。选择一个县级市和一个市辖区分别进行学校划片实验,结果表明：混合元启发算法优化性能优异且收敛性好,适用于求解单校划片和多校划片问题;SPP模型在单校划片问题中具有明显的优势。  相似文献   

13.
This paper presents an intelligent approach to discover transition rules for cellular automata (CA) by using cuckoo search (CS) algorithm. CS algorithm is a novel evolutionary search algorithm for solving optimization problems by simulating breeding behavior of parasitic cuckoos. Each cuckoo searches the best upper and lower thresholds for each attribute as a zone. When the zones of all attributes are connected by the operator ‘And’ and linked with a cell status value, one CS-based transition rule is formed by using the explicit expression of ‘if-then’. With two distinct advantages of efficient random walk of Lévy flights and balanced mixing, CS algorithm performs well in both local search and guaranteed global convergence. Furthermore, the CA model with transition rules derived by CS algorithm (CS-CA) has been applied to simulate the urban expansion of Nanjing City, China. The simulation produces encouraging results, in terms of numeric accuracy and spatial distribution, in agreement with the actual patterns. Preliminary results suggest that this CS approach is well suitable for discovering reliable transition rules. The model validation and comparison show that the CS-CA model gets a higher accuracy than NULL, BCO-CA, PSO-CA, and ACO-CA models. Simulation results demonstrate the feasibility and practicability of applying CS algorithm to discover transition rules of CA for simulating geographical systems.  相似文献   

14.
Analysis of potential spatial behavior in transport infrastructures is usually carried out by means of a digital network. A basic condition for such a network analysis has traditionally been the desire to find solutions to optimization problems and to achieve greater efficiency in industry. Geographic information system (GIS) tools for network analysis are overwhelmingly targeted at finding solutions to optimization problems, which include the shortest path problem and the traveling salesman problem. This article addresses the problem of the lack of tools for finding solutions to a class of constraint satisfaction problems that are of potential interest to behavioral geographers. Constraint satisfaction problems differ from optimization problems in that they lack an expression to be maximized or minimized. We describe how a constraint-based approach to network analysis can be applied to search for ‘excess routes’ that are longer or in other ways exceed single, optimal routes. Our analysis considers both round-trips and travel from A to B and defines a set of constraints that can characterize such paths. We present a labeling algorithm that can generate solutions to such excess route problems.  相似文献   

15.
Limited development ecological zones (LDEZs) are often located in poverty-stricken, ecologically vulnerable areas where ethnic minorities reside. Studies on optimal spatial land-use allocation in LDEZs can promote economic and intensive land use, improve soil quality, facilitate local socioeconomic development, and maintain environmental stability. In this study, we optimized spatial land-use allocations in an LDEZ using the geographic information system (GIS) and a genetic ant colony algorithm (GACA). The multi-objective function considers economic benefits and ecological green equivalents, and improves soil erosion. We developed the GACA by integrating a genetic algorithm (GA) with an ant colony algorithm (ACA). This avoids a large number of redundant iterations and the low efficiency of the GA, and the slow convergence speed of the ACA. The study area is located in Pengyang County, Ningxia, China, which is a typical LDEZ. The land-use data were interpreted from remote sensing (RS) images and GIS. We determined the optimal spatial land-use allocations in the LDEZ using the GACA in the GIS environment. We compared the original and optimal spatial schemes in terms of economic benefits, ecological green equivalents, and soil erosion. The results of the GACA were superior to the original allocation, the ACA, and the multi-objective genetic algorithm, in terms of the optimum, time, and robust performance indexes. We also present some suggestions for the reasonable development and protection of LDEZs.  相似文献   

16.
The timely and secure evacuation of residents to nearby urban emergency shelters is of great importance during unexpected disaster events. However, evacuation and allocation of shelters are seldom examined as a whole, even though they are usually closely related tasks in disaster management. To conduct better spatial allocation of emergency shelters in cities, this study proposes a new method which integrates techniques of multi-agent system and multi-criteria evaluation for spatial allocation of urban emergency shelters. Compared with the traditional emergency shelter allocation methods, the proposed method highlights the importance of dynamic emergency evacuation simulations for spatial allocation suitability analysis. Three kinds of agents involved in evacuation and sheltering procedures are designed: government agents, shelter agents, and resident agents. Emergency evacuations are simulated based on the interactions of these agents to find potential problems, for example, time-consuming evacuation processes and road congestion. A case study in Jing’an District, Shanghai, China was conducted to demonstrate the feasibility of the proposed method. After three rounds of simulation and optimization, new shelters were spatially allocated and a detailed recommended plan of shelters and related facilities was generated. The optimized spatial allocation of shelters may help local residents to be evacuated more quickly and securely.  相似文献   

17.
ABSTRACT

The efficiency of public investments and services has been of interest to geographic researchers for several decades. While in the private sector inefficiency often leads to higher prices, loss of competitiveness, and loss of business, in the public sector inefficiency in service provision does not necessarily lead to immediate changes. In many cases, it is not an entirely easy task to analyze a particular service as appropriate data may be difficult to obtain and hidden in detailed budgets. In this paper, we develop an integrative approach that uses cyber search, Geographic Information System (GIS), and spatial optimization to estimate the spatial efficiency of fire protection services in Los Angeles (LA) County. We develop a cyber-search process to identify current deployment patterns of fire stations across the major urban region of LA County. We compare the results of our search to existing databases. Using spatial optimization, we estimate the level of deployment that is needed to meet desired coverage levels based upon the location of an ideal fire station pattern, and then compare this ideal level of deployment to the existing system as a means of estimating spatial efficiency. GIS is adopted throughout the paper to simulate the demand locations, to conduct location-based spatial analysis, to visualize fire station data, and to map model simulation results. Finally, we show that the existing system in LA County has considerable room for improvement. The methodology presented in this paper is both novel and groundbreaking, and the automated assessments are readily transferable to other counties and jurisdictions.  相似文献   

18.
Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.  相似文献   

19.
针对现阶段各规划边界交叉、空间重叠的问题,本文从提高空间价值、减少空间破碎度和协调各类空间的角度出发,在梳理现有空间优化模型及智能算法的基础上,改进多目标规划模型并适应性改造遗传算法,以此二者构建市级国土空间优化模型。以烟台市为例,设置3种情景为决策者提供方案集进行3类规划主导下的2020年国土空间优化研究,结果显示：①优化后烟台市农业、城镇和生态空间价值分别增加了23.24%、29.27%、6.30%;②不同情景下空间分布合理且较为集中,生态保护情景有利于国土空间集合连片,经济发展情景更适合于多空间协调发展。研究表明：该模型能有效地解决国土空间内容重叠问题,明显提高了国土空间价值,同时优化模型适应性强,为“多规合一”背景下市级国土空间优化提供技术支撑。  相似文献   

20.
Geographic information system (GIS) based methodologies are widely used to various problems. However, its potential for application to strategic maritime search and rescue (SAR) planning remains largely unexplored. To investigate the applicability of GIS-based tools to this problem, this paper presents an approach to evaluate accessibility and response times in a sea area. Such information aids to objectify the response effectiveness of a SAR system, which is important for rational resource allocation. The presented methodology accounts for the main characteristics of maritime response, namely spatial accessibility, capabilities of search and rescue units (SRUs) and prevailing wave conditions, which affect the attainable SRU speeds. An application to the Finnish areas of the Gulf of Finland is shown. Despite the existence of some difficulties with currently available tools (e.g. accurate and user-friendly spatial wave models and challenges with using raster-based methods in topologically complex areas) and limitations in knowledge (e.g. the SRU capabilities in actual operations), the results indicate that the methodology provides good opportunities for enhancing maritime decision making.  相似文献   

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