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tbart (version 1.0)

Teitz and Bart's p-Median Algorithm

Description

Solves Teitz and Bart's p-median problem - given a set of points attempts to find subset of size p such that summed distances of any point in the set to the nearest point in p is minimised. Although generally effective, this algorithm does not guarantee that a globally optimal subset is found.

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Version

Install

install.packages('tbart')

Monthly Downloads

32

Version

1.0

License

GPL (>= 2)

Maintainer

Last Published

February 13th, 2015

Functions in tbart (1.0)

star.diagram

Creates the lines for a 'star diagram'
tb.raw

Teitz-Bart algorithm applied to a 'raw' distance matrix
allocate

Teitz-Bart algorithm applied to Spatial* and Spatial*DataFrame objects
allocations

Teitz-Bart algorithm applied to Spatial* and Spatial*DataFrame objects
mink.dists

Minkowski distances from a Spatial* or Spatial*DataFrame object
tbart-package

Teitz and Bart's $p$-median problem with Spatial* and Spatial*DataFrame objects
tb

Teitz-Bart algorithm applied to Spatial* and Spatial*DataFrame objects
euc.dists

Euclidean distances from a Spatial* or Spatial*DataFrame object