Improving the performance of genetic algorithms for land-use allocation problems

Multi-objective optimization can be used to solve land-use allocation problems involving multiple conflicting objectives. In this paper, we show how genetic algorithms can be improved in order to effectively and efficiently solve multi-objective land-use allocation problems. Our focus lies on improving crossover and mutation operators of the genetic algorithms. We tested a range of different approaches either based on the literature or proposed for the first time. We applied them to a land-use allocation problem in Switzerland including two conflicting objectives: ensuring compact urban development and reducing the loss of agricultural productivity. We compared all approaches by calculating hypervolumes and by analysing the spread of the produced non-dominated fronts. Our results suggest that a combination of different mutation operators, of which at least one includes spatial heuristics, can help to find well-distributed fronts of non-dominated solutions. The tested modified crossover operators did not significantly improve the results. These findings provide a benchmark for multi-objective optimization of land-use allocation problems with promising prospectives for solving complex spatial planning problems.     

Spatial multi-objective land use optimization: extensions to the non-dominated sorting genetic algorithm-II

A spatial multi-objective land use optimization model defined by the acronym ‘NSGA-II-MOLU’ or the ‘non-dominated sorting genetic algorithm-II for multi-objective optimization of land use’ is proposed for searching for optimal land use scenarios which embrace multiple objectives and constraints extracted from the requirements of users, as well as providing support to the land use planning process. In this application, we took the MOLU model which was initially developed to integrate multiple objectives and coupled this with a revised version of the genetic algorithm NSGA-II which is based on specific crossover and mutation operators. The resulting NSGA-II-MOLU model is able to offer the possibility of efficiently searching over tens of thousands of solutions for trade-off sets which define non-dominated plans on the classical Pareto frontier. In this application, we chose the example of Tongzhou New Town, China, to demonstrate how the model could be employed to meet three conflicting objectives based on minimizing conversion costs, maximizing accessibility, and maximizing compatibilities between land uses. Our case study clearly shows the ability of the model to generate diversified land use planning scenarios which form the core of a land use planning support system. It also demonstrates the potential of the model to consider more complicated spatial objectives and variables with open-ended characteristics. The breakthroughs in spatial optimization that this model provides lead directly to other properties of the process in which further efficiencies in the process of optimization, more vivid visualizations, and more interactive planning support are possible. These form directions for future research.     

基于多目标遗传算法的土地利用空间结构优化配置

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。     

Optimal spatial land-use allocation for limited development ecological zones based on the geographic information system and a genetic ant colony algorithm

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.     

基于“多规合一”的市级国土空间优化方法——以烟台市为例

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。     

Optimal spatial allocation of water resources based on Pareto ant colony algorithm

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.     

黑河干流水系水资源优化分配的多目标规划模型

流域水资源综合利用的优化分配是一个多目标决策问题。本文根据黑河干流水系的特点税流域内水资源分配利用的系统分析,详细介绍了黑河干流水系的多目标水资源分配规划模型,研制的模型考虑了水资源开发利用的国民经济发展和流域环境质量二方面的目标,按分区设计了工业、农业、林业、牧业(灌溉草场)、生态林草地和城镇、人畜生活用水等六个用水户,分别给出地表水和地下水二种配水量。通过二套数据计算,证明黑河干流水系多目标水资源分配规模模型可为流域合理开发利用水资源提供定量配水依据。     

对机构改革背景下空间规划体系构建的思考

“建立空间规划体系”是自然资源部的一项重要职能,也是整合空间规划、保障空间治理机制有效运行的必然要求。在借鉴国外空间规划体系的基础上,按照适应中国政治体制和法律基础、适应未来空间开发和空间治理变化的需求,提出构建层层传导的空间规划体系确保国家重大战略部署得以落实;提出在微观尺度空间规划进行空间开发权与土地利用权的分配,作为实施空间用途管制的法律依据,保障地方多样化、灵活化的发展;通过构建“宏观政策性/指导性规划—中观衔接性规划—微观实施性规划”的空间规划体系,为国家建立和完善空间规划体系、提升空间治理能力提供参考。     

城市新区教育设施可达性评价与空间优化——以深圳市坪山区为例

城市新区在发展过程中面临教育设施供给不足和不均衡的问题,可达性与空间优化方法能够为解决该问题提供科学依据。以深圳市坪山区为例,从供需关系出发,运用高斯两步移动搜寻法和改进的p-中位模型,探讨城市新区教育设施的可达性评价与空间优化,提出优化迫切度概念,分析得到教育设施优化区位和规模。结果表明:坪山区各层级教育设施可达性均存在明显空间差异;优化迫切度结果能够为设施配置的重点区域及优先次序提供依据;优化后各层级教育设施分布比较均衡,与人口分布较为契合;优化结果反映出相关规划标准存在不适用性,应注重规划标准差异化的研究。将城市教育设施空间布局评价和区位优化相结合,能为深圳市坪山区教育设施布局规划提供科学依据。     

Optimal spatial allocation of irrigation water under uncertainty using the bilayer nested optimisation algorithm and geospatial technology

The optimal spatial allocation of irrigation water under uncertainty has become a serious concern because of irrigation water shortage and uncertain factors that affect irrigation water allocation. In this study, an optimal multi-objective model for irrigation water allocation under uncertainty is developed to maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation. The original and optimal plantation structure, irrigation mode and soil water content are acquired through geospatial technology. A bilayer nested optimisation (BLNO) algorithm is designed to produce multiple individuals of design vectors using an ant colony neural network algorithm for an outer optimisation. Meanwhile, a continuous adaptive ant colony (CAAC) algorithm is used for inner optimisation to calculate the interval values of the uncertain model. The crop distribution and irrigation mode are obtained to parameterise the planting area and the water demand of each crop and each block in the multi-objective model. This model is then solved and analysed. Compared to the optimal schemes obtained from an inexact two-stage fuzzy-stochastic programming and the CAAC, respectively, BLNO can effectively and efficiently solve the optimal spatial allocation of irrigation water under uncertainty. This method can spatially maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation using lower and upper bound maps whilst visually obtaining the exact crop type, reasonable irrigation method and precise water demand for each block and for the entire irrigated area.     

面向国土空间规划的乡村空间治理机制与路径

城乡国土空间统-用途管制背景下,乡村空间治理成为国土空间治理体系的重要组成部分.从乡村空间治理的理论内涵出发,构建了乡村空间治理理论分析框架,探讨了乡村空间治理作用于国土空间规划的内在机制和可行路径.结论 如下:①乡村空间治理是以乡村空间为治理对象,通过规划和协商等方式,实现乡村空间用途有效管制,空间权利有序配置,凸显...     

重庆市主城都市区人口老龄化与养老服务资源配置空间错位研究

基于县域尺度下第七次人口普查数据,构建养老服务资源配置综合指数,利用泰尔指数、空间错位指数以及地理探测器,从匹配性角度探讨重庆市主城都市区人口老龄化和养老服务资源配置的协调关系及其驱动机制。结果表明：1）2020年重庆市主城都市区人口老龄化系数与老年人口数量的空间分布特征基本一致,呈现从中心城区到主城新区由内至外增加的圈层结构特征;2）2020年重庆市主城都市区养老服务资源配置空间分布不均衡,中心城区形成养老服务资源配置评价高地,主城新区形成养老服务资源配置评价低值环;3）2020年重庆市主城都市区人口老龄化与养老服务资源配置存在空间错位现象,中心城区资源过剩与主城新区资源不足的矛盾突出;4）政府政策、居民收入水平以及产业结构的区域差异对养老服务资源的协调发展具有显著的正向影响,而市场经济规模的扩大、家庭规模的缩小以及人口结构的变动未能有效推动养老服务资源协调发展。     

An agent-based model for optimal land allocation (AgentLA) with a contiguity constraint

Spatial optimization is complex because it usually involves numerous spatial factors and constraints. The optimization becomes more challenging if a large set of spatial data with fine resolutions are used. This article presents an agent-based model for optimal land allocation (AgentLA) by maximizing the total amount of land-use suitability and the compactness of patterns. The essence of the optimization is based on the collective efforts of agents for formulating the optimal patterns. A local and global search strategy is proposed to inform the agents to select the sites properly. Three sets of hypothetical data were first used to verify the optimization effects. AgentLA was then applied to the solution of the actual land allocation optimization problems in Panyu city in the Pearl River Delta. The study has demonstrated that the proposed method has better performance than the simulated annealing method for solving complex spatial optimization problems. Experiments also indicate that the proposed model can produce patterns that are very close to the global optimums.     

A spatial genetic algorithm for automating land partitioning

Land fragmentation is a widespread situation which may often hinder agricultural development. Land consolidation is considered to be the most effective land management planning approach for controlling land fragmentation and hence improving agricultural efficiency. Land partitioning is a basic process of land consolidation that involves the subdivision of land into smaller sub-spaces subject to a number of constraints. This paper explains the development of a module called LandParcelS (Land Parcelling System) that is a part of an integrated planning and decision support system called LACONISS (LAndCONsolidation Integrated Support System) which has been developed to assist land consolidation planning in Cyprus. LandParcelS automates the land partitioning process by designing and optimising land parcels in terms of their shape, size and value. The methodology integrates geographical information systems and a genetic algorithm that has been applied to two land blocks that are part of a larger case study area in Cyprus. Partitioning is treated as either a single or multi-objective problem for various optimisation cases. The results suggest that a step forward has been made in solving this complex spatial problem, although further research is needed to improve the algorithm. This approach may have relevance to other spatial planning tasks that involve single or multi-objective optimisation problems, especially those dealing with space partitioning.     

空间管治视角下京津冀协同发展类型区划

京津冀协同发展的核心是基于问题导向和底线思维,打破行政区划,在更大区域尺度上优化资源配置,实现区域整体发展目标。因此,从优化空间规划体系的高度,开展京津冀区域协同发展的类型区划和类型区管理,实现分区施策的精细化管治极为重要。本文首先立足于京津冀区域发展差异,利用空间属性双聚类的方法将京津冀划分为中部核心功能引领区、东部沿海重点发展区、南部门户功能拓展区、西部和北部生态涵养保护区等四大区域;然后以区县为最小分析单元,从现状开发强度、用地增量预测和生态保护责任等三大维度构建类型划分指标体系,并利用三维空间坐标划分方法将京津冀划分为五大类型区,即：城镇优化发展区、城镇重点拓展区、现代农业发展区、适度建设发展区和严格生态保护区;最后,在空间管治视角下提出京津冀区域分区管治与区域协同管理的建议。     

欧盟空间规划研究进展及启示

欧盟空间规划是世界上最早的跨国空间规划。其新的空间规划理念、跨国规划实践、新的规划方法与制度等,在世界空间规划领域产生了较大的影响。欧盟从上世纪80年代以来先后启动实施了欧洲标准区域划分(NUTS)、欧洲空间发展远景(ESDP)和欧洲空间规划研究计划(SPESP)等3个不同的空间规划研究项目,在空间规划理念、空间区域划分等方面取得了重要的研究成果。此外,欧洲区域发展基金、欧洲社会基金、结构基金以及监测评估网络的建立,是欧盟空间规划实施的重要政策保障体系。文章最后进一步探讨了欧盟空间规划实践对我国当前空间规划研究的若干启示。     

An integrated approach for addressing geographic uncertainty in spatial optimization

There exist many facets of error and uncertainty in digital spatial information. As error or uncertainty will not likely ever be completely eliminated, a better understanding of its impacts is necessary. Spatial analytical approaches, in particular, must somehow address data-quality issues. This can range from evaluating impacts of potential data uncertainty in planning processes that make use of methods to devising methods that explicitly account for error/uncertainty. To date, little has been done to structure methods accounting for error. This article develops an integrated approach to address data uncertainty in spatial optimization. We demonstrate that it is possible to characterize uncertainty impacts by constructing and solving a new multi-objective model that explicitly incorporates facets of data uncertainty. Empirical findings indicate that the proposed approaches can be applied to evaluate the impacts of data uncertainty with statistical confidence, which moves beyond popular practices of simulating errors in data.     

转型发展期“多规合一”理论认知与技术方法

中国工业化、城镇化已进入转型发展新阶段,创新驱动发展与体制机制约束的矛盾加剧,资源短缺性及其配置低效性日益凸显,“多规合一”受到各级政府和学术界的广泛关注。推进“多规合一”,创新区域规划理论与技术方法,构建中国特色的国土空间规划体系成为当前全面深化改革的重要议题之一。本文深入分析了中国“多规不一”现实问题,总结了“多规”矛盾的本质特征,探讨了“多规合一”的战略定位,构建了“三主三分”的“多规合一”基本理论框架,提出了“三步走”多规逐步调适的技术途径及其长效机制。“多规合一”的核心在于从区域空间优化的战略高度统筹协调各项规划,科学引导城乡土地优化配置,实现“多规”在空间上的同一性、在功能上的融合性、在发展过程中的协同性。“多规合一”的重点是推进形成一个总分有序、层级清晰、职能精准的区域规划体系。     

广州市土地利用结构优化配置及其潜力

基于广州市土地利用结构、地区经济、生态与社会特点,结合广州城市总体规划(2010-2020),对广州市域土地利用结构进行生态经济效益-自然生态效益导向的多目标优化配置研究。结果表明：对广州市土地利用数量结构进行调整,一定时间内能够满足地区可持续发展;但是,土地仍然承担着巨大的压力,焦点是建设用地和农用地之间的数量转变,以耕地为主,也包括对未利用土地的利用;土地利用潜力度模型结果显示,通过优化土地利用结构,土地系统的协调度增大而潜力度减小：在生态经济效益目标下,潜力度分别为0.628～0.661,0.372～0.339;在自然生态效益目标下,分别为0.531～0.782,0.469～0.218,表明土地利用系统将趋于更高的协调状态,而其数量结构优化配置的潜力减小,优化各产业部门内部土地资源结构及其空间布局,将是广州市土地资源高效集约利用和进一步挖潜的主导方向。     

A land-use mix allocation model considering adjacency,intensity, and proximity

ABSTRACT

Land-Use Mix (LUM) refers to the strategy of integrating complementary functions within a building or area. While LUM has become a dominant approach in urban planning, its actual benefits and vision for spatial planning remain unclear. To clarify this issue, this study discerns the spatial features of land-use patterns depending on the compatibilities among land-use categories. Accordingly, this study introduces three LUM measures – adjacency, intensity, and proximity – to identify differences in the spatial distribution of land-use categories. Based on these measures, a land-use allocation model is developed to specify spatial patterns satisfying the given compatibilities. This model is tested by applying the concept of the neighborhood unit on a case study of normative land-use patterns subject to specified compatibilities. The results describe spatial features of four compatibility sets, including a set exhibiting a compatibility conflict between the same land-use pair and LUM measures when, for example, a given land-use pair is compatible in terms of intensity but incompatible in terms of proximity. Understanding the spatial features of a normative land-use pattern that satisfies various possible compatibilities will facilitate the incorporation of the LUM approach into local planning guidance and zoning ordinances.