Combinatorial Optimization for Urban Planning: Strategic Demolition of Abandoned Houses in Baltimore, MD
Philip Garboden (),
Amitabh Basu and
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Philip Garboden: Department of Urban and Regional Planning, University of Hawaiâ€˜i at Manoa
Lenny Fan: Department of Applied Math and Statistics, Johns Hopkins University
Tamas Budavari: Department of Applied Math and Statistics, Johns Hopkins University
Amitabh Basu: Department of Applied Math and Statistics, Johns Hopkins University
John Evans: Department of Housing and Community Development, Baltimore City
No 2019-5, Working Papers from University of Hawaii Economic Research Organization, University of Hawaii at Manoa
In 2017, Baltimore City was awarded $75 million dollars earmarked for the targeted demolition of a portion of its 16,000 vacant and aban- doned buildings. Selecting an optimal set of demolition targets is difficult given that the cost per demolition is not independent of the overall demolition pattern; like many older cities, Baltimoreâ€™s aban- doned housing includes a large number of attached rowhouses, which require the construction of retaining walls when a demolished home abuts a non-demolished home. In this paper, we present a method by which planners can use integer linear programming to identify optimal demolition targets for a number of potential objectives. The simplest objective, demolishing the maximum number of houses for a specific budget, is compared to more complex functions that attempt to proxy improved quality of life resulting from the demolitions. The results of different objective functions are then assessed in terms of equity and efficiency using the spatial distribution of proposed targets as a point of comparison.
Pages: 27 pages
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