Defining Equitable Geographic Districts in Road Networks via Stable Matching

We introduce a novel method for defining geographic districts in road networks using stable matching. In this approach, each geographic district is defined in terms of a center, which identifies a location of interest, such as a post office or polling place, and all other network vertices must be labeled with the center to which they are associated. We focus on defining geographic districts that are equitable, in that every district has the same number of vertices and the assignment is stable in terms of geographic distance. That is, there is no unassigned vertex-center pair such that both would prefer each other over their current assignments. We solve this problem using a version of the classic stable matching problem, called symmetric stable matching, in which the preferences of the elements in both sets obey a certain symmetry. In our case, we study a graph-based version of stable matching in which nodes are stably matched to a subset of nodes denoted as centers, prioritized by their shortest-path distances, so that each center is apportioned a certain number of nodes. We show that, for a planar graph or road network with $n$ nodes and $k$ centers, the problem can be solved in $O(n\sqrt{n}\log n)$ time, which improves upon the $O(nk)$ runtime of using the classic Gale-Shapley stable matching algorithm when $k$ is large. Finally, we provide experimental results on road networks for these algorithms and a heuristic algorithm that performs better than the Gale-Shapley algorithm for any range of values of $k$.Comment: 9 pages, 4 figures, to appear in 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2017) November 7-10, 2017, Redondo Beach, California, US

Economic Impacts of GO TO 2040

The economy of the Chicago metropolitan region has reached a critical juncture. On the one hand, Chicagoland is currently a highly successful global region with extraordinary assets and outputs. The region successfully made the transition in the 1980s and 1990s from a primarily industrial to a knowledge and service-based economy. It has high levels of human capital, with strong concentrations in information-sector industries and knowledge-based functional clusters -- a headquarters region with thriving finance, business services, law, IT and emerging bioscience, advanced manufacturing and similar high-growth sectors. It combines multiple deep areas of specialization, providing the resilience that comes from economic diversity. It is home to the abundant quality-of-life amenities that flow from business and household prosperity.On the other hand, beneath this static portrait of our strengths lie disturbing signs of a potential loss of momentum. Trends in the last decade reveal slowing rates, compared to other regions, of growth in productivity and gross metropolitan product. Trends in innovation, new firm creation and employment are comparably lagging. The region also faces emerging challenges with respect to both spatial efficiency and governance.In this context, the Chicago Metropolitan Agency for Planning (CMAP) has just released GO TO 2040, its comprehensive, long-term plan for the Chicago metropolitan area. The plan contains recommendations aimed at shaping a wide range of regional characteristics over the next 30 years, during which time more than 2 million new residents are anticipated. Among the chief goals of GO TO 2040 are increasing the region's long-term economic prosperity, sustaining a high quality of life for the region's current and future residents and making the most effective use of public investments. To this end, the plan addresses a broad scope of interrelated issues which, in aggregate, will shape the long-term physical, economic, institutional and social character of the region.This report by RW Ventures, LLC is an independent assessment of the plan from a purely economic perspective, addressing the impacts that GO TO 2040's recommendations can be expected to have on the future of the regional economy. The assessment begins by describing how implementation of GO TO 2040's recommendations would affect the economic landscape of the region; reviews economic research and practice about the factors that influence regional economic growth; and, given both of these, articulates and illustrates the likely economic impacts that will flow from implementation of the plan. In the course of reviewing the economic implications of the plan, the assessment also provides recommendations of further steps, as the plan is implemented, for increasing its positive impact on economic growth

New Applications of the Nearest-Neighbor Chain Algorithm

The nearest-neighbor chain algorithm was proposed in the eighties as a way to speed up certain hierarchical clustering algorithms. In the first part of the dissertation, we show that its application is not limited to clustering. We apply it to a variety of geometric and combinatorial problems. In each case, we show that the nearest-neighbor chain algorithm finds the same solution as a preexistent greedy algorithm, but often with an improved runtime. We obtain speedups over greedy algorithms for Euclidean TSP, Steiner TSP in planar graphs, straight skeletons, a geometric coverage problem, and three stable matching models. In the second part, we study the stable-matching Voronoi diagram, a type of plane partition which combines properties of stable matchings and Voronoi diagrams. We propose political redistricting as an application. We also show that it is impossible to compute this diagram in an algebraic model of computation, and give three algorithmic approaches to overcome this obstacle. One of them is based on the nearest-neighbor chain algorithm, linking the two parts together

Final strategic plan for statewide GIS technology coordination in South Carolina : volume I: GIS background and business case

This plan's purpose is to provide direction and focus for improved GIS coordination and expanded use of GIS technology in South Carolina. This Strategic Plan follows a detailed GIS Needs Assessment and successful coordination work carried out by CGI since its creation in 1996. This Strategic Plan provides a long-term vision for statewide GIS coordination and use. The specific goals and work elements cover a 5-year period

On the computational tractability of a geographic clustering problem arising in redistricting

Redistricting is the problem of dividing a state into a number $k$ of regions, called districts. Voters in each district elect a representative. The primary criteria are: each district is connected, district populations are equal (or nearly equal), and districts are "compact". There are multiple competing definitions of compactness, usually minimizing some quantity. One measure that has been recently promoted by Duchin and others is number of cut edges. In redistricting, one is given atomic regions out of which each district must be built. The populations of the atomic regions are given. Consider the graph with one vertex per atomic region (with weight equal to the region's population) and an edge between atomic regions that share a boundary. A districting plan is a partition of vertices into $k$ parts, each connnected, of nearly equal weight. The districts are considered compact to the extent that the plan minimizes the number of edges crossing between different parts. Consider two problems: find the most compact districting plan, and sample districting plans under a compactness constraint uniformly at random. Both problems are NP-hard so we restrict the input graph to have branchwidth at most $w$. (A planar graph's branchwidth is bounded by its diameter.) If both $k$ and $w$ are bounded by constants, the problems are solvable in polynomial time. Assume vertices have weight~1. One would like algorithms whose running times are of the form $O(f(k,w) n^c)$ for some constant $c$ independent of $k$ and $w$, in which case the problems are said to be fixed-parameter tractable with respect to $k$ and $w$). We show that, under a complexity-theoretic assumption, no such algorithms exist. However, we do give algorithms with running time $O(c^wn^{k+1})$. Thus if the diameter of the graph is moderately small and the number of districts is very small, our algorithm is useable

BIDding on cities: Applying the Business Improvement District model for urban sustainability

There is a growing expectation in the field of sustainable development that cities are the most suitable scale for addressing global environmental issues, particularly through their ability to mobilize local actors. Business improvement districts (BIDs) are a form of public-private partnership (PPP) in cities typically established by associations of private actors that aim to generate value in communities by jointly investing in physical improvements and local services. The model is gaining attention in Sweden, with one BID established in the Sofielund neighborhood of Malmö currently integrating sustainable development concepts into its core strategy to experiment with solutions for reducing socioeconomic inequalities and the area’s environmental impacts. Since BID Sofielund is seeking to learn new methods for incorporating sustainability and because the nexus between BIDs and sustainability has not been adequately addressed in the academic literature, this research utilizes an exploratory approach in a multiple-case study design focusing on BID Sofielund and four reference cases to investigate how BIDs engage with sustainability through the projects and processes they carry out and develops potential explanations for why they might choose to do so. By plotting BID activities in a sustainability framework, this study found that BIDs contribute to sustainable development through strategies including providing a platform for collaborative governance, promoting energy efficiency in buildings, investing in capital improvement projects that enhance public spaces, and filling gaps in social service provision. The study identified multiple contributors to why BIDs engage in sustainability and assembled a general framework consisting of both internal and external drivers that must be considered to fully understand BID sustainability activities, however more research is needed. From an academic standpoint, the knowledge produced furthers the discussion on BIDs in a sustainability context and it provides practical value for BID practitioners as they seek to measure performance in new ways and enhance their effectiveness through sustainability-driven strategies

Cities Building Community Wealth

As cities struggle with rising inequality, widespread economic hardship, and racial disparities, something surprising and hopeful is also stirring. In a growing number of America's cities, a more inclusive, community-based approach to economic development is being taken up by a new breed of economic development professionals and mayors. This approach to economic development could be on the cusp of going to scale. It's time it had a name. We call it community wealth building

Consumer Data Research

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies