I have a question regarding how to run a quadratically constrained minimisation problem in Mosek (from Matlab). This is my problem
Suppose that the linear equality and inequality constraints are not there. The Mosek documentation (here) explains well how to implement the optimisation problem. First, we should rewrite the problem as
Second, we should set
clear prob;
% Specify the linear objective terms.
prob.c = [0, -1, 0];
% Specify the quadratic terms of the constraints.
prob.qcsubk = [1 1 1 1 ]';
prob.qcsubi = [1 2 3 3 ]';
prob.qcsubj = [1 2 3 1 ]';
prob.qcval = [-2.0 -2.0 -0.2 0.2]';
% Specify the quadratic terms of the objective.
prob.qosubi = [1 2 3 3 ]';
prob.qosubj = [1 2 3 1 ]';
prob.qoval = [2.0 0.2 2.0 -1.0]';
% Specify the linear constraint matrix
prob.a = [1 1 1];
% Specify the lower bounds
prob.blc = [1];
prob.blx = [-3;-3;-4];
prob.ulx = [3;3;5];
[r,res] = mosekopt('minimize',prob);
Question: how can I introduce in the code above the two linear equality and inequality constraints in my example?
I have tried to look at examples on linear programming but they do not seem to easily mix with my code above.
