The MOSEK Python optimizer API manual Version 7.0 (Revision 141)

A.2. CLASS TASK 299
markj : mark
The value of markj[j] specifies for which bound (upper or lower) on variable subj[j]
sensitivity analysis should be performed.
rightpricei : double[]
rightpricei[i] is the right shadow price for the upper/lower bound (indicated by marki[i])
of the constraint with index subi[i].
rightpricej : double[]
rightpricej[j] is the right shadow price for the upper/lower bound (indicated by marki[j])
on variable subj[j] .
rightrangei : double[]
rightrangei[i] is the right range for the upper/lower bound (indicated by marki[i]) of
the constraint with index subi[i].
rightrangej : double[]
rightrangej[j] is the right range for the upper/lower bound (indicated by marki[j]) on
variable subj[j].
subi : int[]
Indexes of bounds on constraints to analyze.
subj : int[]
Indexes of bounds on variables to analyze.
Description:
Calculates sensitivity information for bounds on variables and constraints.
For details on sensitivity analysis and the definitions of shadow price and linearity interval see
chapter 15.
The constraints for which sensitivity analysis is performed are given by the data structures:
• subi Index of constraint to analyze.
• marki Indicate for which bound of constraint subi[i] sensitivity analysis is performed. If
marki[i] = mark.up the upper bound of constraint subi[i] is analyzed, and if marki[i]
= mark.lo the lower bound is analyzed. If subi[i] is an equality constraint, either mark.lo
or mark.up can be used to select the constraint for sensitivity analysis.
Consider the problem:
Suppose that
minimize x 1 + x 2
subject to − 1 ≤ x 1 − x 2 ≤ 1,
x 1 = 0,
x 1 ≥ 0, x 2 ≥ 0
• numi = 1;
• subi = [0];