CoinMPSolver did the whole job in one function: sample the model by
perturbing each variable, build the CoinMP matrix from those
coefficients, solve, and read the result back. Move the matrix
build and solve into a standalone helper, coinmpSolveLinearModel,
that takes the sampled coefficients plus the variable bounds and
column types and returns the solution and status.
The helper treats the first entry of each cell's coefficient vector
as the value of an affine model at the origin and the rest as the
per variable slopes, which is what the existing sampling already
produces. That keeps the same convention while letting a future
caller supply coefficients sampled around a different point and its
own bounds, which is what a sequential linear programming loop
needs.
No behaviour change. CoinMPSolver still samples and sets up bounds
and column types exactly as before, then calls the helper. The
CoinMP solver unit test passes unchanged.
Signed-off-by: Tomaž Vajngerl <tomaz.vajngerl@collabora.co.uk>
Change-Id: I6d373a48caa9d67a932a599068368bae978f1f22
Reviewed-on: https://gerrit.collaboraoffice.com/c/online/+/4648
Tested-by: Tomaž Vajngerl <tomaz.vajngerl@collabora.com>
Reviewed-by: Miklos Vajna <vmiklos@collabora.com>
(cherry picked from commit 197f790a93880f56dd53db43e6bbb61c22ccfdc2)
Reviewed-on: https://gerrit.libreoffice.org/c/core/+/208337
Reviewed-by: Xisco Fauli <xiscofauli@libreoffice.org>
Tested-by: Xisco Fauli <xiscofauli@libreoffice.org>
Tomaž Vajngerl
2c87d392dc