High-Performance Open-Source Archive
extract_constraints() previously created explicit 0
values in the sparse matrix. They are now implicit.get_solution returns incorrect
results on R version < 4. Affected package versions are
1.0.0 and 1.0.1. (#404)TRUE are
not added to the model, as they are always satisfied. Likewise,
constraints that evaluate to FALSE throw an error.
Previously specifying a constraint without a variable would have caused
a run time error.3.4 as {ompr.roi}
has the same minimum R version.additional_solver_output() is now an exported
function.MIPModel. It should now be faster, more
maintainable, more stable and it has fewer bugs.sum_over, a replacement for sum_expr
in the MIPModelset_bounds for MIPModel now accepts
(in)equalities as well (#365)MIPModel now supports characters as variable
indexessolution object has a new named entry called
additional_solver_output. In that place solver packages,
like ompr.roi can store arbitrary solver information.
Including solver specific messages and status codes. It should be read
using the function additional_solver_output().solution can now have the
solver_status = "success" which is used by the most recent
ompr.roi version.sum_expr
failed (#327)add_variable failed if indexes were
in the wrong order (#266)All listed functions will likely be removed at some later point the future.
sum_expr shall not be used anymore. Please use
sum_over instead.MIPLModel will likely be removed from the package, as
the vectorized approach did lead to some problems. Please use
MIPModel instead.add_variable_, add_constraint_,
set_objective_, set_bounds and
get_solution_ are not needed anymore with the new
MIPModel as it is powered by rlang..show_progress_bar parameter is now deprecated in
all functions.extract_constraints now always returns a sparse matrix,
even if there are 0 constraints or variables.data.frame returned with
get_solution(x[i, j]) has slightly changed in special
cases, but for the majority of calls, it should stay the same. One of
these special cases is if you created your variable similar to
add_variable(model, x[i, j], j = ..., i = ...), where the
indexes in the variable and the quantifiers have different orderings. In
general, please do not depend on the ordering of the rows, but use the
indexes to retrieve the correct value. For example by sorting the
data.frame , before reading.colwise in the experimental MILPModel
backend.sum_expr now produce a warning
instead of an error. The missing indexes will be ignored (#202).get_solution could return mixed up
values when variables had partially similar names (eg: s[i]
and bus[i]) by @hugolarzabal (#244).length != 1.data.table
versionsdplyr dependencyMILPModel, a new, vectorized backend for mixed
integer linear programs that can handle very large models. It will
eventually replace MIPModel.get_column_duals,
get_row_duals) to extract the dual (column and row) values
from an LP.3.2.0get_solution now always return a solution, even if the
solution status is not optimal.get_solution has a third argument type
with permitted values being “primal” and “dual” to return the respective
column primal or dual values.ompr now uses sparse constraint matrices.
extract_constraints now returns a sparse matrix and
objective_function returns a sparse vector.3.3.0Rcpp. The minimum Rcpp
version is now 0.12.12progress package.
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