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

Chapter 10
Problem formulation and solutions
In this chapter we will discuss the following issues:
• The formal definitions of the problem types that MOSEK can solve.
• The solution information produced by MOSEK.
• The information produced by MOSEK if the problem is infeasible.
10.1 Linear optimization
A linear optimization problem can be written as
where
minimize
c T x + c f
subject to l c ≤ Ax ≤ u c ,
l x ≤ x ≤ u x ,
(10.1)
• m is the number of constraints.
• n is the number of decision variables.
• x ∈ R n is a vector of decision variables.
• c ∈ R n is the linear part of the objective function.
• A ∈ R m×n is the constraint matrix.
• l c ∈ R m is the lower limit on the activity for the constraints.
• u c ∈ R m is the upper limit on the activity for the constraints.
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