A Multiobjective Optimization Model for Locating Affordable Housing Investments While Maximizing Accessibility to Jobs by Public Transportation
Published In
Environment and Planning B: Urban Analytics and City Science
Document Type
Citation
Publication Date
7-20-2017
Abstract
This paper develops a new optimal location model for siting affordable housing units to maximize the accessibility of low-income workers to appropriate jobs by public transportation. Transitaccessible housing allows disadvantaged populations to reduce their reliance on automobiles, which can lead to savings on transportation-related expenditures. The housing location model developed here maximizes transit accessibility while reducing the clustering of affordable housing units in space. Accessibility is maximized using a high-resolution space-time metric of public transit accessibility, originally developed for service equity analysis. The second objective disperses subsidized housing projects across space using a new minimax dispersion model based on spatial interaction principles. The multiobjective model trades off accessibility maximization and affordable housing dispersion, subject to upper and lower bounds on the land acquisition and construction budget. The model is tested using data for Tempe, AZ including actual data for vacant parcels, travel times by light rail and bus, and the location of low-wage jobs. This model or similar variants could provide insightful spatial decision support to affordable-housing providers or tax-credit administrators, facilitating the design of flexible strategies that address multiple social goals.
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DOI
10.1177/2399808317719708
Persistent Identifier
https://archives.pdx.edu/ds/psu/26542
Citation Details
Zhong, Q., Karner, A., Kuby, M., & Golub, A. (2017). A multiobjective optimization model for locating affordable housing investments while maximizing accessibility to jobs by public transportation. Environment and Planning B: Urban Analytics and City Science.
Description
© The Author(s) 2017
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