I have an optimization problem with a lot of rotated_lorentz(1) constrains:

cvx_begin

…

maximize(lambda)

H*x == lambda*r

for i = 0:N

{x(1+i*3),a(i+1)-x(2+i*3),b(i+1)-x(3+i*3)} == rotated_lorentz(1);
{x(1+i*3),c(i+1)+x(2+i

*3),d(i+1)+x(3+i*3)} == rotated_lorentz(1);

end

cvx_end

CVX is using about 95% of the total computation time and Mosek is using about 2%.

Is there a way to improve the performance of CVX for this problem?

I have tried to formulated the constrains as, many semidefinite(2) and as one semidefinite.