arXiv subjects

Drew Horton

Publications and source records attributed to Drew Horton.

3 recordsLinked to original sources

arXiv2024

Evacuation Planning on Time-Expanded Networks with Integrated Wildfire Information

We study the problem of evacuation planning for natural disasters, focusing on wildfire evacuations. By creating pre-planned evacuation routes that can be updated based on real-time data, we provide an easily adjustable approach to evacuation planning and implementation. Our method uses publicly available data and can be tailored for a particular region or circumstance. We formulate large-scale evacuations as maximum flow problems on time-expanded networks, in which we integrate hazard information given in the form of a shapefile. An initial flow and evacuation plan is found based on a predicted fire, and is then updated based on revised fire information received during the evacuation. We provide a proof of concept on three locations with historic deadly fires using data available through OpenStreetMaps, a basemap for a geographic information system (GIS), on a NetworkX Python script. The results validate viable running times and quality of information for application in practice. Particular strengths are the scalability and modularity of our approach and accompanying software package.

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arXiv2024

Hundreds of grocery outlets needed across the United States to achieve walkable cities

The notion of the $x$-minute city is again popular in urban planning, but the practical implications of developing walkable neighborhoods have not been rigorously explored. What is the scale of the challenge that cities needing to retrofit face? Where should new stores or amenities be located? For 500 cities in the United States, we explored how many additional supermarkets would be required to achieve various levels of $x$-minute access and where new stores should be located so that this access is equally-distributed. Our method is unique because it combines a novel measure of equality with a new model that optimally locates amenities for inequality-minimizing community access. We found that 25% of the studied cities could reach 15-minute access by adding five or fewer stores, while only 10% of the cities could even achieve 5-minute average access when using neighborhood centroids as potential sites; the cities that could, on average, required more than 100 stores each. This work provides a tool for cities to use evidenced-based planning to efficiently retrofit in order to enable active transport, benefiting both the climate and their residents' health. It also highlights the major challenge facing our cities due to the existing and ongoing car-dependent urban design that renders these goals unfeasible.

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arXiv2024

A scalable optimization approach for equitable facility location: Methodology and transportation applications

Efficient and equitable access to essential services, such as healthcare, food, and education, is an important goal in urban planning, public policy, and transport logistics. However, existing facility location models often do not scale well to large instances, or primarily focus on optimizing average accessibility, neglecting equity concerns, particularly for disadvantaged populations. This paper proposes a novel, scalable framework for equitable facility location, introducing a linearized proxy for the Kolm-Pollak Equally-Distributed Equivalent (EDE) metric to balance efficiency and fairness. Computational experiments demonstrate that our approach scales to extremely large problem instances, while being sensitive enough to account for inequity throughout the distribution, not merely via the maximum value. Moreover, optimal solutions represent significant improvements for the worst-off residents in terms of distance to an open amenity, while also attaining a near-optimal average experience for all users. An extensive real-world case study on supermarket access illustrates the practical applicability of the framework, with additional examples coming from polling applications. As such, the model is extended to handle real-world considerations such as capacity constraints, split demand assignments, and location-specific penalties. By bridging the gap between equity theory and practical optimization, this work offers a robust and versatile tool for researchers and practitioners in urban planning, transportation, and public policy.

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