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 language | English |
|---|---|
| Pages (from-to) | 149-173 |
| Number of pages | 25 |
| Journal | Socio-Economic Planning Sciences |
| Volume | 35 |
| Issue number | 3 |
| DOIs | |
| State | Published - 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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