Purpose
Fixes all the MIP entities to the values of the last found MIP solution. This is useful for finding the reduced costs for the continuous variables after the MIP entities have been fixed to their optimal values.
Synopsis
problem.fixmipentities(options)
Argument
|
options
|
Options for fixing the MIP entities, evaluated as a bit string whose bits have the following meaning:
|
Bit
|
Meaning
|
|
0
|
If all MIP entities should be rounded to the nearest discrete value in the solution before being fixed.
|
|
1
|
If piecewise linear and general constraints should be kept in the problem with only the non-convex decisions (i.e. which part of a non-convex piecewise linear function or which variable attains a maximum) fixed. Otherwise all variables appearing in piecewise linear or general constraints will be fixed.
|
|
Example
This example performs a tree search on problem
myprob and then uses
fixmipentities before solving the remaining linear problem:
p.read("myprob", "")
p.mipoptimize()
p.fixmipentities(1)
p.lpoptimize()
p.writeprtsol()
Further information
1. Because of tolerances, it is possible for e.g. a binary variable to be slightly fractional in the MIP solution, where it might have the value
0.999999 instead of being at exactly
1.0. With
ifround = 0, such a binary will be fixed at
0.999999, but with
ifround = 1, it will be fixed at
1.0.
2. This command is useful for inspecting the reduced costs of the continuous variables in a problem after the MIP entities have been fixed. Sensitivity analysis can also be performed on the continuous variables in a MIP problem using
problem.rhssa or
problem.objsa after calling
fixmipentities.
Related topics
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