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

5.2. LINEAR OPTIMIZATION 25
and the bounds
lj x ≤ x j ≤ u x j , j = 0, . . . , n − 1, (5.3)
where we have used the problem elements:
m and n
which are the number of constraints and variables respectively,
x
c
which is the variable vector of length n,
which is a coefficient vector of size n
⎡
c = ⎣
c 0
c n−1
⎤
⎦ ,
c f
A
which is a constant,
which is a m×n matrix of coefficients is given by
l c and u c
⎡
A = ⎣
a 0,0 · · · a 0,(n−1)
⎤
· · ·
⎦ ,
which specify the lower and upper bounds on constraints respectively, and
l x and u x
which specifies the lower and upper bounds on variables respectively.
Please note the unconventional notation using 0 as the first index rather than 1. Hence, x 0 is the first
element in variable vector x. This convention has been adapted from Python arrays which are indexed
from 0.
5.2.1 Example: Linear optimization
The following is an example of a linear optimization problem: