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Spatial optimization for land acquisition problems: A review of models, solution methods, and GIS support
Author(s) -
Xiao Ningchuan,
Murray Alan T.
Publication year - 2019
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12545
Subject(s) - heuristic , metaheuristic , computer science , field (mathematics) , geographic information system , spatial analysis , data science , management science , operations research , data mining , mathematical optimization , geography , artificial intelligence , cartography , engineering , remote sensing , mathematics , pure mathematics
This article reviews the interdisciplinary research field of spatial optimization for land acquisition problems. We start with a theoretical framework to identify three categories of spatial optimization models: problems with aspatial constraints, location models, and problems with topological constraints. Exact, heuristic, and metaheuristic approaches to solving these problems are critically discussed. Tools that are available in commercial and open‐source GIS packages are reviewed from four aspects. We first survey the off‐the‐shelf support and then the development environments in these packages. A case study of the one‐center problem is used to illustrate the computational performance of different solution methods. Finally the advantages and disadvantages of current GIS data models are discussed. The article concludes with challenges and future directions for solving spatial optimization problems for land acquisition.