Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto

The dataset used in this paper is a collection of 31 Neighbourhood Improvement Areas (NIAs) in Toronto, Canada. Each NIA has a set of residential locations, candidate allocation locations, and existing amenities. The dataset is used to evaluate the effectiveness of the Walkability Optimization algorithm in improving walkability in underserved neighbourhoods.

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Weimin Huang, Elias B. Khalil (2025). Dataset: Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto. https://doi.org/10.57702/blxhlecl

DOI retrieved: January 2, 2025

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Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.2212.05192
Author Weimin Huang
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Elias B. Khalil
Homepage https://github.com/khalil-research/walkability