problem.addcols
problem.addcols |
Purpose
Add columns to the problem after passing it to the Optimizer using the input routines.
Synopsis
problem.addcols (objx, mstart, mrwind, dmatval, bdl, bdu, names, types)
Arguments
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objx
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Array containing the objective function coefficients of the new columns.
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mstart
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Array containing the offsets in the
mrwind and
dmatval arrays of the start of the elements for each column.
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mrwind
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Array containing the row indices for the elements in each column.
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dmatval
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Array containing the element values.
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bdl
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Array containing the lower bounds on the added columns.
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bdu
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Array containing the upper bounds on the added columns.
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names
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(optional) Array containing the names of the columns added.
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types
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(optional) Array of characters containing the types of the newly added columns:
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Example
In this example, we consider the two problems:
| (a) | maximize: | 2x + y | (b) | maximize: | 2x + y + 3z | |||||
| subject to: | x + 4y | ≤ | 24 | subject to: | x + 4y + 2z | ≤ | 24 | |||
| y | ≤ | 5 | y + z | ≤ | 5 | |||||
| 3x + y | ≤ | 20 | 3x + y | ≤ | 20 | |||||
| x + y | ≤ | 9 | x + y + 3z | ≤ | 9 | |||||
| z | ≤ | 12 |
Using
addcols, the following transforms (a) into (b):
p = xpress.problem ()
p.read ("example.lp")
# assume this problem has at least four constraints
p.addcols (obj = [3], mstart = [0,3], mrwind = [0, 1, 3],
matval = [2,1,3], bdl = [-xpress.infinity], bdu = [12],
names = ['john_cleese'], types = ['C'])
Further information
1. The constant
xpress.infinity can be used to represent infinite bounds.
2. If the columns are added to a MIP problem, then they will be continuous variables unless
types is specified. Use
problem.chgcoltype to impose integrality conditions on such new columns.
Related topics