c(
person("Scott", "Chamberlain", role = c("aut", "cre"),
email = "myrmecocystus@gmail.com", comment = c(ORCID="0000-0003-1444-9135")),
person("Ignasi", "Bartomeus", role = "aut", email = "nacho.bartomeus@gmail.com")
)
species, native, invasive, origin, web, API,
eol, gisd, nsr, itis, griis
Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>),
Ignasi Bartomeus [aut]

Get species origin data (whether species is native/invasive) from the
following sources on the web: Encyclopedia of Life (<http://eol.org>), Flora
'Europaea' (<http://rbg-web2.rbge.org.uk/FE/fe.html>), Global Invasive Species
Database (<http://www.iucngisd.org/gisd>), the Native Species Resolver
(<https://bien.nceas.ucsb.edu/bien/tools/nsr/>), Integrated Taxonomic
Information Service (<https://www.itis.gov/>), and Global Register of
Introduced and Invasive Species (<http://www.griis.org/>).
crul, jsonlite, data.table, xml2, taxize (>= 0.9.0)

The package deals with Operations Research LOCational Analysis models
This version of the package deals with the min-sum or center location problems.
The min-sum location problem search for a point such that the weighted sum of the distances to the demand points are minimized.

The package deals with Operations Research LOCational Analysis
models
This version of the package deals with the min-sum ocation
problem, also known as Fermat--Weber problem or center location
problem. The min-sum location problem search for a point such
that the weighted sum of the distances to the demand points are
minimized.

This version of the package deals with the min-sum
location problem, also known as Fermat--Weber problem.  The
min-sum location problem search for a point such that the
weighted sum of the distances to the demand points are
minimized.

grDevices, graphics, knitr, rmarkdown, stats
Operations Research LOCational Analysis Models
Objects and methods to handle and solve the min-sum location problem, also known as Fermat-Weber problem. The min-sum location problem search for a point such that the weighted sum of the distances to the demand points are minimized. See "The Fermat-Weber location problem revisited" by Brimberg, Mathematical Programming, 1, pg. 71-76, 1995. <DOI:10.1007/BF01592245>.
General global optimization algorithms are used to solve the problem, along with the adhoc Weiszfeld method, see "Sur le point pour lequel la Somme des distances de n points donnes est minimum", by Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pg. 355-386, 1937 or "On the point for which the sum of the distances to n given points is minimum", by E. Weiszfeld and F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.