@article{assunccao2006efficient,
  title={Efficient Regionalization Techniques for Socio-economic Geographical Units Using Minimum Spanning Trees},
  author={Assun{\c{c}}{\~a}o, Renato M. and Neves, Marcos Corr{\^e}a and C{\^a}mara, Gilberto and da Costa Freitas, Corina},
  journal={International Journal of Geographical Information Science},
  volume={20},
  number={7},
  pages={797--811},
  year={2006},
  publisher={Taylor \& Francis},
  doi={10.1080/13658810600665111}
}

@article{duque2012max,
  author={Duque, Juan C. and Anselin, Luc and Rey, Sergio J.},
  title={THE MAX-P-REGIONS PROBLEM*},
  journal={Journal of Regional Science},
  volume={52},
  number={3},
  pages={397--419},
  doi={10.1111/j.1467-9787.2011.00743.x},
  url={https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9787.2011.00743.x},
  eprint={https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-9787.2011.00743.x},
  abstract={ABSTRACT In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value. We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.},
  year={2012}
}

@article{koopmans1949optimum,
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@article{murray2021contemporary,
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  year={2021},
  publisher={Elsevier},
  doi={10.1016/j.omega.2019.102176}
}

@article{wei2020efficient,
  title={Efficient Regionalization for Spatially Explicit Neighborhood Delineation},
  author={Wei, Ran and Rey, Sergio J. and Knaap, Elijah},
  journal={International Journal of Geographical Information Science},
  pages={1--17},
  year={2020},
  publisher={Taylor \& Francis},
  doi={10.1080/13658816.2020.1759806}
}

@article{openshaw1977geographical,
  title={A Geographical Solution to Scale and Aggregation Problems in Region-building, Partitioning and Spatial Modelling},
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@article{openshaw1995algorithms,
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@article{pysal2007,
  author={Sergio J. Rey and Luc Anselin},
  title={{PySAL: A Python Library of Spatial Analytical Methods}},
  journal={The Review of Regional Studies},
  year=2007,
  volume={37},
  number={1},
  pages={5-27},
  keywords={Open Source; Software; Spatial},
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}

@article{rey2015open,
  title={Open geospatial analytics with PySAL},
  author={Rey, Sergio J. and Anselin, Luc and Li, Xun and Pahle, Robert and Laura, Jason and Li, Wenwen and Koschinsky, Julia},
  journal={ISPRS International Journal of Geo-Information},
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  number={2},
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  year={2015},
  publisher={Multidisciplinary Digital Publishing Institute},
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}

@article{Rey2021,
  author={Rey, Sergio J. and Anselin, Luc and Amaral, Pedro and Arribas-Bel, Dani and Cortes, Renan Xavier and Gaboardi, James David and Kang, Wei and Knaap, Elijah and Li, Ziqi and Lumnitz, Stefanie and Oshan, Taylor M. and Shao, Hu and Wolf, Levi John},
  title={{The PySAL Ecosystem: Philosophy and Implementation}},
  journal={Geographical Analysis},
  year={2021},
  doi={10.1111/gean.12276},
  abstract={PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction to the library as it stands now, as well as the scientific and conceptual underpinnings of its core set of components. Finally, we provide a prospective look at the library's future evolution.}
}

@article{wolf2020,
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}

@article{Toregas1971,
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}

@article{Church1974,
  author={Church, Richard L. and ReVelle, C.S.},
  doi={10.1111/j.1435-5597.1974.tb00902.x},
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  pages={101--118},
  title={{The Maximal Covering Location Problem}},
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}

@article{ReVelle1970,
  author={ReVelle, C.S. and Swain, R.W.},
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@article{Hakimi1964,
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  doi={10.1287/opre.12.3.450},
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  pages={450--459},
  pmid={8598587},
  title={{Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph}},
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}

@misc{spopt2021,
    author    = {Feng, Xin, and Gaboardi, James D. and Knaap, Elijah and Rey, Sergio J. and Wei, Ran},
    month     = {jan},
    year      = {2021},
    title     = {{pysal/spopt}},
    url       = {https://github.com/pysal/spopt},
    doi       = {10.5281/zenodo.4444156},
    keywords  = {python,regionalization,spatial-optimization,location-modeling}
}

@article{mitchell2011pulp,
  title={{PuLP: A Linear Programming Toolkit for Python}},
  author={Mitchell, Stuart and OSullivan, Michael and Dunning, Iain},
  journal={The University of Auckland, Auckland, New Zealand},
  volume={65},
  year={2011}
}

@article{badr2015tool,
  title={A tool for hierarchical climate regionalization},
  author={Badr, Hamada S. and Zaitchik, Benjamin F. and Dezfuli, Amin K.},
  journal={Earth Science Informatics},
  volume={8},
  number={4},
  pages={949--958},
  year={2015},
  publisher={Springer},
  doi={10.1007/s12145-015-0221-7}
}

@article{LEMUSCANOVAS2019114,
    title = {synoptReg: An R package for computing a synoptic climate classification and a spatial regionalization of environmental data},
    journal = {Environmental Modelling \& Software},
    volume = {118},
    pages = {114--119},
    year = {2019},
    issn = {1364-8152},
    doi = {10.1016/j.envsoft.2019.04.006},
    url = {https://www.sciencedirect.com/science/article/pii/S1364815219300064},
    author = {Marc Lemus-Canovas and Joan A. Lopez-Bustins and Javier Martin-Vide and Dominic Royé},
    keywords = {Alps, Environmental regionalization, R package, synoptReg, Synoptic classification},
}

@article{Chen2021,
    title = {{Open-Source Approaches for Location Cover Models: Capabilities and Efficiency}},
    journal = {Journal of Geographical Systems},
    volume = {23},
    pages = {361--380},
    year = {2021},
    issn = {1435-5949},
    doi = {10.1007/s10109-021-00350-w},
    author = {Chen, Huanfa and Murray, Alan T. and Jiang, Rui},
}

@article{daru2020phyloregion,
  title={{phyloregion: R package for biogeographical regionalization and macroecology}},
  author={Daru, Barnabas H. and Karunarathne, Piyal and Schliep, Klaus},
  journal={Methods in Ecology and Evolution},
  volume={11},
  number={11},
  pages={1483--1491},
  year={2020},
  doi={10.1111/2041-210X.13478}
}

@article{regioneR2015,
    author = {Gel, Bernat and Díez-Villanueva, Anna and Serra, Eduard and Buschbeck, Marcus and Peinado, Miguel A. and Malinverni, Roberto},
    title = {{regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests}},
    journal = {Bioinformatics},
    volume = {32},
    number = {2},
    pages = {289--291},
    year = {2015},
    month = {09},
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btv562},
}

@misc{nsRFA,
    author    = {Viglione, A.},
    year      = {2009},
    title     = {{nsRFA: Non-supervised Regional Frequency Analysis}},
    url       = {http://www.CRAN.R-project.org/package=nsRFA},
}

@misc{rgeoda,
  title = {rgeoda: R Library for Spatial Data Analysis},
  author = {Li, Xun and Anselin, Luc},
  year = {2022},
  url  = {https://github.com/geodacenter/rgeoda/},
}

@article{rahman2018sdpt3r,
    author = {Rahman, Adam},
    year = {2019},
    month = {01},
    pages = {371},
    title = {{sdpt3r: Semidefinite Quadratic Linear Programming in R}},
    volume = {10},
    journal = {The R Journal},
    doi = {10.32614/RJ-2018-063}
}

@misc{RBGL,
    author    = {Carey, V. and Long, L. and Gentleman, R.},
    year      = {2022},
    title     = {{RBGL: An interface to the BOOST graph library}},
    url       = {https://www.bioconductor.org/packages/release/bioc/html/RBGL.html},
}

@misc{pyspatialopt,
    author    = {Pulver, Aaron},
    year      = {2016},
    title     = {{pyspatialopt: A library to create, solve, and analyze spatial optimization problems}},
    url       = {https://github.com/apulverizer/pyspatialopt},
}

@misc{allagash,
    author    = {Pulver, Aaron},
    year      = {2019},
    title     = {{allagash: A spatial optmization library for covering problems}},
    url       = {https://github.com/apulverizer/allagash},
}

@misc{maxcovr,
    author    = {Tierney, N.},
    year      = {2019},
    title     = {{maxcovr: A Set of Tools for Solving the Maximal Covering Location Problem}},
    url       = {https://github.com/njtierney/maxcovr},
}

@article{scikitlearn,
    title={{Scikit-learn: Machine Learning in Python}},
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            Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
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    year={2011},
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}