The Maximal Covering Problem with Some Negative Weights

This article presents the maximal covering problem on a network when some of the weights can be negative. Integer programming formulations are proposed and tested with ILOG CPLEX. Heuristic algorithms, an ascent algorithm, and simulated annealing are proposed and tested. The simulated annealing approach provides the best results for a data set comprising 40 problems.     

A Genetic Approach to Detecting Clusters in Point Data Sets

Spatial analysis techniques are widely used throughout geography. However, as the size of geographic data sets increases exponentially, limitations to the traditional methods of spatial analysis become apparent. To overcome some of these limitations, many algorithms for exploratory spatial analysis have been developed. This article presents both a new cluster detection method based on a genetic algorithm, and Programs for Cluster Detection, a toolkit application containing the new method as well as implementations of three established methods: Openshaw's Geographical Analysis Machine (GAM), case point-centered searching (proposed by Besag and Newell), and randomized GAM (proposed by Fotheringham and Zhan). We compare the effectiveness of cluster detection and the runtime performance of these four methods and Kulldorf's spatial scan statistic on a synthetic point data set simulating incidence of a rare disease among a spatially variable background population. The proposed method has faster average running times than the other methods and significantly reduces overreporting of the underlying clusters, thus reducing the user's postprocessing burden. Therefore, the proposed method improves upon previous methods for automated cluster detection. The results of our method are also compared with those of Map Explorer (MAPEX), a previous attempt to develop a genetic algorithm for cluster detection. The results of these comparisons indicate that our method overcomes many of the problems faced by MAPEX, thus, we believe, establishing that genetic algorithms can indeed offer a viable approach to cluster detection.     

Restructuring old industrial and inner urban areas: A contrastive analysis of state policies in Great Britain and Germany

This paper deals with two outstanding forms of state intervention devised to cope with structural change in old industrial areas: Urban Development Corporations (UDCs) in Great Britain and the Emscher Park International Building Exhibition (IBA) in the Ruhr district in Germany. In Sections 2 and 3, we deal with UDCs and the IBA separately, concentrating on their history, objectives, modes of operation, financial arrangements, and their relationship with other heal and state agencies. Furthermore, these two policies are related to the general political and social situation in Britain and Germany. In Section 4, we compare the IBA with UDCs directly, discussing whether these schemes can be considered a success with regard to their own objectives. Of particular importance is the role of the local level and the opportunity for various actors, interest groups and public bodies to participate in the process of restructuring. Finally, we reflect upon the implications for planning in general emanating from the IBA and UDCs. One important result of our research is that the very broad approach behind the IBA — despite certain inherent contradictions — will do more justice to the multi‐faceted problems of old industrial areas than the concept of ‘regeneration’ behind UDCs.     

Inter‐person Separation: A New Objective Standard for Evaluating the Spatial Fairness of Political Redistricting Plans

The fundamental basis for territorial political representation is the presumption that people share greater common interests with others in closer geographic proximity than with people farther away. This principle is found in U.S. legal requirements that districts for the House of Representatives and state legislatures should not needlessly divide “communities of interest” and should be “reasonably compact.” We propose a new objective standard to evaluate spatial fairness of redistricting plans: the extent to which a delineation minimizes total distance between all pairs of people assigned to the same district. To date, the legal standard of compactness has primarily been thought of in terms of the shapes of political districts, but boundary shape may have little correspondence with how populations are actually clustered and dispersed. Inter‐person separation, by contrast, provides a direct, intuitive metric for evaluating the congruence of districting plans with the territorial basis of political representation. To operationalize an inter‐person separation standard, we propose a model and present a heuristic method for delineating comparator districting schemes. We apply the standard to the current U.S. Congressional Districts in the states of Arizona and North Carolina to demonstrate how inter‐person separation could be used to develop and vet future redistricting plans.     

Two New Location Covering Problems: The Partial P-Center Problem and the Partial Set Covering Problem

Two new covering problems are introduced. The partial covering P-center problem minimizes a coverage distance in such a way that a given fraction of the population is covered. The partial set covering problem seeks the minimum number of facilities needed to cover an exogenously specified fraction of the population within a given coverage distance. The problems are formulated as integer linear programming problems. Bisection search algorithms are outlined for the two problems. The search algorithm repeatedly solves a Lagrangian relaxation of the maximal covering problem. Computational results for the Lagrangian relaxation of the maximal covering problem and for the bisection search algorithms are presented on problems with up to 150 nodes.     

Two New Location Covering Problems: The Partial P-Center Problem and the Partial Set Covering Problem

Two new covering problems are introduced. The partial covering P-center problem minimizes a coverage distance in such a way that a given fraction of the population is covered. The partial set covering problem seeks the minimum number of facilities needed to cover an exogenously specified fraction of the population within a given coverage distance. The problems are formulated as integer linear programming problems. Bisection search algorithms are outlined for the two problems. The search algorithm repeatedly solves a Lagrangian relaxation of the maximal covering problem. Computational results for the Lagrangian relaxation of the maximal covering problem and for the bisection search algorithms are presented on problems with up to 150 nodes.     

Probabilistic Regionalization via Evidence Accumulation with Random Spanning Trees as Weak Spatial Representations

Spatial clusters contain biases and artifacts, whether they are defined via statistical algorithms or via expert judgment. Graph-based partitioning of spatial data and associated heuristics gained popularity due to their scalability but can define suboptimal regions due to algorithmic biases such as chaining. Despite the broad literature on deterministic regionalization methods, approaches that quantify regionalization probability are sparse. In this article, we propose a local method to quantify regionalization probabilities for regions defined via graph-based cuts and expert-defined regions. We conceptualize spatial regions as consisting of two types of spatial elements: core and swing. We define three distinct types of regionalization biases that occur in graph-based methods and showcase the use of the proposed method to capture these types of biases. Additionally, we propose an efficient solution to the probabilistic graph-based regionalization problem via performing optimal tree cuts along random spanning trees within an evidence accumulation framework. We perform statistical tests on synthetic data to assess resulting probability maps for varying distinctness of underlying regions and regionalization parameters. Lastly, we showcase the application of our method to define probabilistic ecoregions using climatic and remotely sensed vegetation indicators and apply our method to assign probabilities to the expert-defined Bailey's ecoregions.     

关于我国环境税收法制建设的思考

随着我国经济发展步伐的加快,环境污染问题也日益严重,而我国现行环境税费制度存在较多问题,不能很好地起到防治污染、保护环境的作用。本文在分析我国设立环境税的价值基础上,探讨了我国环境税收方面存在的诸多问题并提出相关法律对策。     

基于凝胶法的古代壁画表面加固材料的去除技术模拟研究

为了延长古代壁画的寿命,保护工作者通常将一些现代高分子材料渗透到壁画颜料层,用以黏结加固濒危的壁画。这些材料对壁画的保护发挥了积极作用。但是随着时间的推移,有些材料已经开始劣化,逐渐丧失作用,有的甚至会加速壁画的破坏。因此,古代壁画表面失效加固材料的清除技术已经成为文物保护需要解决的重要科学技术问题。本项研究针对中国古代壁画4种常用黏结加固高分子材料,聚醋酸乙烯乳液、纯丙烯酸乳液、有机硅改性丙烯酸乳液和Paraloid B72树脂,开展了清除技术的实验室模拟研究。本工作使用目前最环保和高效的水凝胶清洗技术,设计制备了4种凝胶材料,制成16个凝胶配方,结合乙酸乙酯、对二甲苯、正戊醇、碳酸丙烯酯等清洗剂,从凝胶的工作性能、凝胶与清洗剂的相容性、清洗剂对壁画表面层的破坏性、对4种粘结加固材料的清除能力,以及粘结加固材料老化对去除率的影响等方面,在瓷板、玻片和模拟壁画上开展了系列实验研究,从中筛选出分别适合于清除这4种常用高分子材料的凝胶清洗方法,计算了去除率,初步摸清了相关技术数据。     

An Equivalence Theorem to Integrate Entropy-Maximizing Submodels within Overall Mathematical-Programming Frameworks

This paper presents a lemma and a theorem which demonstrate equivalent ways of formulating certain mathematical-programming problems. The first shows, in general terms, how constraints can be “absorbed” into the objective function and vice versa. The second shows how such ideas can be applied to spatial analysis problems involving the minimization of development costs subject to interactions being determined by (suboptimal) entropy-maximizing models. This provides both a new perspective on the relationship between programming and entropy models, and formulations that are computationally convenient.     

Analyzing Cross-classified Data with Inherent Spatial Dependence

Despite considerable recent progress in the methods available for the log-linear analysis of categorical data arising from complex sampling schemes, only a few papers have been published that deal with the parallel phenomenon of dependence induced by spatial sampling. This paper aims to add to the general awareness of this topic and suggests some new ideas for tackling the problems raised. In the paper it is shown that the method that has been proposed for the valid selection of log-linear models given spatially dependent data and some derivative methods are somewhat conservative when compared to an approach based on a model of spatial dependence outlined in section 4. The method also serves as a data exploratory technique to enhance the use of the more robust conservative approach.     

A Note on Applying the Gravity Rule to the Airline Hub Problem

In this note we propose a new model for the airline hub selection problem. Passengers use a hub on the way to their destination. We apply the objective of minimizing the total miles traveled by passengers. This formulation can be used as the basis for other objectives also.     

AN ALGORITHM FOR THE SPATIAL PRICE EQUILIBRIUM PROBLEM ON A GENERAL NETWORK IN THE SPACE OF THE PATH FLOWS*

ABSTRACT. The spatial price equilibrium on a general network may be formulated as a nonlinear-cost mathematical programming problem with simple constraints, when the decision variables are the path flows. The solution of this problem is difficult due to the very large number of variables (paths) and the impracticality of generating all the paths from all the origins to all the destinations. In this paper, we develop a Gauss-Seidel-Newton Projection algorithm and combine it with a restriction strategy. That makes it unnecessary to generate a priori all the paths. This algorithm may be further improved by exploiting the equivalence between the spatial price equilibrium on a general network and the network equilibrium. Computational results that we present in this paper demonstrate the efficiency of the proposed solution algorithms.     

THE LAST RIGHTS: MORE ON ARCHAEOLOGY AND THE DEAD

Summary. In a recent paper, one of us (Bahn 1984) made a preliminary sketch of the main issues involved in the question of whether archaeologists have the right to disturb the dead. Since then, a number of important new case studies have featured prominently in the media, and more literature on the subject has started to appear—most notably a collection of papers (Green 1984) which, though focused on the particular problems of North America, contains much food for thought for archaeologists elsewhere. In this article we propose to look at the new data and consider what light moral philosophy can throw on the problem as a whole.     

Collaborating with the Machines: A Hybrid Method for Classifying Policy Documents

Governments produce vast and growing quantities of freely available text: laws, rules, budgets, press releases, and so forth. This information flood is facilitating important, growing research programs in policy and public administration. However, tightening research budgets and the information's vast scale forces political science and public policy to aspire to do more with less. Meeting this challenge means applied researchers must innovate. This article makes two contributions for practical text coding—the process of sorting government text into researcher-defined coding schemes. First, we propose a method of combining human coding with automated computer classification for large data sets. Second, we present a well-known algorithm for automated text classification, the Naïve Bayes classifier, and provide software for working with it. We argue and provide evidence that this method can help applied researchers using human coders to get more from their research budgets, and we demonstrate the method using classical examples from the study of policy agendas.     

Aggregation Decomposition and Aggregation Guidelines for a Class of Minimax and Covering Location Models

Facility location problems often involve movement between facilities to be located and customers/demand points, with distances between the two being important. For problems with many customers, demand point aggregation may be needed to obtain a computationally tractable model. Aggregation causes error, which should be kept small. We consider a class of minimax location models for which the aggregation may be viewed as a second‐order location problem, and use error bounds as aggregation error measures. We provide easily computed approximate “square root” formulas to assist in the aggregation process. The formulas establish that the law of diminishing returns applies when doing aggregation. Our approach can also facilitate aggregation decomposition for location problems involving multiple “separate” communities.     

Dispersion of Nodes Added to a Network

For location problems in which optimal locations can be at nodes or along arcs but no finite dominating set has been identified, researchers may desire a method for dispersing p additional discrete candidate sites along the m arcs of a network. This article develops and tests minimax and maximin models for solving this continuous network location problem, which we call the added-node dispersion problem (ANDP). Adding nodes to an arc subdivides it into subarcs. The minimax model minimizes the maximum subarc length, while the maximin model maximizes the minimum subarc length. Like most worst-case objectives, the minimax and maximin objectives are plagued by poorly behaved alternate optima. Therefore, a secondary MinSumMax objective is used to select the best-dispersed alternate optima. We prove that equal spacing of added nodes along arcs is optimal to the MinSumMax objective. Using this fact we develop greedy heuristic algorithms that are simple, optimal, and efficient (O( mp )). Empirical results show how the maximum subarc, minimum subarc, and sum of longest subarcs change as the number of added nodes increases. Further empirical results show how using the ANDP to locate additional nodes can improve the solutions of another location problem. Using the p-dispersion problem as a case study, we show how much adding ANDP sites to the network vertices improves the p-dispersion objective function compared with (a) network vertices only and (b) vertices plus randomly added nodes. The ANDP can also be used by itself to disperse facilities such as stores, refueling stations, cell phone towers, or relay facilities along the arcs of a network, assuming that such facilities already exist at all nodes of the network.     

Recursive Estimation of the Spatial Error Model

In this paper, we propose a recursive approach to estimate the spatial error model. We compare the suggested methodology with standard estimation procedures and we report a set of Monte Carlo experiments which show that the recursive approach substantially reduces the computational effort affecting the precision of the estimators within reasonable limits. The proposed technique can prove helpful when applied to real-time streams of geographical data that are becoming increasingly available in the big data era. Finally, we illustrate this methodology using a set of earthquake data.     

An efficient interchange procedure for the archaeological seriation problem

This paper considers the archaeological seriation problem defined over incidence matrices. Two procedures adapted from interchange algorithms for the travelling salesman problem are described and tested on 31 problems extracted from the literature. The better of these two procedures consistently yields excellent solutions and appears to outperform previous algorithms.     

AUTOMATIC MINIMIZATION OF THE RIGIDITY ECCENTRICITY OF 3D REINFORCED CONCRETE BUILDINGS

The objective of this paper is to obtain the optimum design of 3D reinforced concrete buildings in terms of their performance under earthquake loading. This goal is achieved by considering the minimisation of the eccentricity between the mass centre and the rigidity centre of each storey layout as the optimisation objective in order to produce torsionally balanced structures. This problem is considered as a combined topology and sizing optimisation problem. The location and the size of the columns and the shear walls of the structure of each storey layout constitute the design variables. Apart from the constraints imposed by the seismic and reinforced concrete structure design codes, architectural restrictions are also taken into account. The test examples showed that a reduction in the structural cost of the building is achieved by minimising the eccentricity between the mass centre and the rigidity centre of each storey layout. Evolutionary optimisation algorithms and in particular a specially tailored algorithm based on Evolution Strategies is implemented for the solution of this type of structural optimisation problems.