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Tenant-based subsidized housing location planning under uncertainty

  • Carnegie Mellon University

Research output: Contribution to journal › Article › peer-review

Abstract

Subsidized housing policy in the United States must increasingly account for a greater use of tenant-based housing subsidies in place of traditional high-rise public housing. This paper focuses on design of policies to assist families relocating from high-rise public housing to rent-subsidized market-rate housing that, in principle, offers more flexibility in consumption and mobility. These policies must incorporate uncertainty in the residential choices of families already using tenant-based subsidies. A multi-objective stochastic integer program for relocation planning is formulated where it is shown that the model can be made linear and solved using chance-constrained programming. Preliminary computational results show that this model, while requiring significant amounts of information on housing mobility and housing markets, can be solved in a straightforward way. Model outputs clearly display tradeoffs between competing objectives and provide decisionmakers with more realistic alternatives for policy development.

Original languageEnglish
Pages (from-to)149-173
Number of pages25
JournalSocio-Economic Planning Sciences
Volume35
Issue number3
DOIs
StatePublished - 2001

ASJC Scopus Subject Areas

  • Geography, Planning and Development
  • Economics and Econometrics
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

Keywords

  • Integer programming
  • Mathematical programming
  • Multi-objective programming
  • Stochastic programming
  • Subsidized housing
  • Uncertainty

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