This release is created to assist in replicating previous journal articles that used this software. The API of maxcovr is likely to change from here.
max_coverage_relocationnow works for different data, thanks to a bug fix.
gurobi, in addition to
lpSolve. Testing still to be conducted.
coverageadded as a one liner to take two dataframes and from the coverage of one dataframe on another. Documentation and tests still need work
relocationmethods. This will eventially be an S3 method, I think?
max_coverage, replacing them with key functions. This will make things easier to debug and extend in the future. These functions start with
extract_. There will likely be some updates to this in the future
max_coveragefunctions to work with vectors, this fule is called
maxcovr-refactor-vectors. This provides some more efficient computation of preparation of matrices for optimisation, and will provide substantial speedups for larger N, and for when multiple
n_added’s are needed.
max_coveragenow returns the entire solution from
lpSolve, except for the constraints, because they are too large (can easily be over 1Gb)
summary.maxcovr_relocationmethod now return information about the previous distances.
max_coverage_relocationso that it plays better with extracting summary information.
max_coverage_relocation, takes a arguments for total cost, installation cost, and relocation costs and then works out how many facilities it can place, and potentially remove and replace to obtain optimum coverage. The function is currently under development. In the future it will be absorted into
added a results extraction method for
extract_mc_result_relocation. Eventually this will be be absorbed into the
extract_mc_result function, through some kind of S3 method.
summary S3 method for
max_coverage_relocation, and an
is.maxcovr, which should be handy for testing.
nearestto find the nearest lat/long points from one dataframe to another and then calculate the distance between the two. This is at least 10 times faster than the previous method using joins and dplyr.
max_coverageto include the
extract_mc_resultinside the function, rather than needing a separate function call. This was to save space, as the A matrix and friends can be rather large, especially if you are running the coverage multiple times under different conditions.
coverage_distance, which allows you to specify the coverage you are interested in, and
nearest, where you specify
nearestto be “facility” if you want the nearest facility to each user, “user” if you want the nearest user to each facility, and NULL if you just want the complete pairwise distances.
NEWS.mdfile to track changes to the package.
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