gbp3d_solver_dpp {gbp} | R Documentation |
gbp3d_solver_dpp
Description
solve gbp3d via extreme point heuristic and best information score fit strategy.
Usage
gbp3d_solver_dpp(p, ldh, m)
Arguments
p |
p profit of it fit into bn <vector> - cluster max(l, d) and min(l, d) via gbp3d_solver_dpp_prep_create_p() |
ldh |
it position and scale <matrix> - l, d, h it scale along x, y, z, subject to orientation rotation <numeric> |
m |
bn scale <vector> - l, d, h bn scale along x, y, z <numeric> |
Details
gbp3d init a profit vector p, a length vector l, a depth vector d, a height vector h, and also a length constraint ml, a depth constraint md, and a height constraint mh on l x d x h cuboid with geometry intepretation.
gbp3d solver would solve
maximize sum_j=1^n p_j k_j
subject to fit (l_j, d_j, h_j) at coordinate (x_j, y_j, z_j) such that no overlap in ml x md x mh cuboid, j = 1, ......, n
and instantiate a gbp3d object with a x-axis coordinate vector x, a y-axis coordinate vector y, a z-axis coordinate vector z, a selection vector k, and an objective o.
Value
gbp3d a gbp3d instantiate with p profit, it item (x, y, z, l, d, h) position scale matrix, bn bin (l, d, h) scale vector, k selection, o objective, and ok an indicator of all fit or not.
See Also
Other gbp3d: gbp3d_checkr
,
gbp3d