A multiobjective optimization model for locating affordable housing investments while maximizing accessibility to jobs by public transportation

Qing Zhong, Alex Karner, Michael Kuby, Aaron Golub

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

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. Transit-accessible 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.

Original languageEnglish (US)
Pages (from-to)490-510
Number of pages21
JournalEnvironment and Planning B: Urban Analytics and City Science
Volume46
Issue number3
DOIs
StatePublished - Mar 1 2019

Keywords

  • Affordable housing
  • accessibility
  • facility dispersion
  • location
  • optimization

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Urban Studies
  • Architecture
  • Management, Monitoring, Policy and Law
  • Nature and Landscape Conservation

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