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- W2528996 abstract "Recent advances in microprocessor technology have made it possible to find mathematically optimal solutions for school facility planning. Beginning with accurate forecasts based on historical data (such as those available through gradient search, cohort survival methodologies), and supplemented by future-oriented methodologies (such as traditional land use studies), it is possible to gauge expected future growth in a school system and to allocate that growth to specific regions. By disaggregating growth to the building attendance-area level and comparing that disaggregation to building capacities, the out-ofcapacity (OOC) status for each building for each future year can be determined. By color coding the OOC status for each building for any one year, a computer generated map can be used to examine geographic relationships of OOC problems. Here the most significant recent advance in technology comes to bear upon the problem --finding the optimal location for capital projects (new construction, expansion, replacement, or closing). Using a nonlinear discrete optimizer (such as GAMS 2.25, driving MINOS 5 *) the geographic coordinates of new schools can be identified, and the selection of existing schools for capital projects can be specified, such that transportation is minimized and all other mathematically specified school board policies are honored (racial balance, overcrowding, etc.). Finally, simple binary programming can be used to fix the attendance boundaries for all new and existing schools, assuming that student locations or addresses have previously been geocoded." @default.
- W2528996 created "2016-06-24" @default.
- W2528996 creator A5071615914 @default.
- W2528996 date "1995-01-01" @default.
- W2528996 modified "2023-09-25" @default.
- W2528996 title "Geographic Information and School Facility Planning" @default.
- W2528996 cites W596228433 @default.
- W2528996 doi "https://doi.org/10.1007/978-0-387-34839-1_21" @default.
- W2528996 hasPublicationYear "1995" @default.
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