The maximum value decreases with iterations when I use an iterative scheme to solve a succession of CVX problems

1

Hello everybody ! I have made a maximum problem and put the result to next iteration for its initial point, however, the optimum value decreases with iterations, do someone konw the reason? Because I have exponential cone in some expressions so I use Mosek 9.2.35.

This is my code:

cvx_begin
variables eta_trj q_1cvx(N,2) q_2cvx(N,2) T_U1(N) T_U2(N) S_U1(n) S_U2(n)
maximize (eta_trj)
subject to
(1/(N-1))(sum(Rlb_BU1(2:N))-(N-1)log(sig2)/log(2)-sum(RT_U1(2:N))) >= eta_trj;
for n = 2:N
T_U1(n) <= square_pos(norm(qr_1(n,:)-r_1)) + 2(qr_1(n,:)-r_1)((q_1cvx(n,1:2)-qr_1(n,:)).’)+H^2;
T_U1(n) >= H^2;
end
for n = 1:(N-1)
norm(q_1cvx(n+1,1:2)-q_1cvx(n,1:2)) <= S_max;
end
norm(q_1cvx(N,1:2)-F_1) <= S_max;
norm(q_1cvx(1,1:2)-i_1) <= S_max;
cvx_end

These are results:
1-th iteration

Status: Solved
Optimal value (cvx_optval): -0.963634

And I put the optimum value into 2-th iteration and produce results as below:

Status: Solved
Optimal value (cvx_optval): -1.70507

Who has any idea about this situation? Thanks!

2

I used to think the optimum value will increase with iterations.

3

This situation happens when I add this line

for n = 2:N
T_U1(n) <= square_pos(norm(qr_1(n,:)-r_1)) + 2(qr_1(n,:)-r_1)((q_1cvx(n,1:2)-qr_1(n,:)).’)+H^2;
T_U1(n) >= H^2;
end

And the optimum value will increase when I put optimum value into next iteration as below:
1-th iteration without these lines

Status: Solved
Optimal value (cvx_optval): +3.75116

And I put the optimum value into 2-th iteration and produce results as below:

Status: Solved
Optimal value (cvx_optval): +8.77856

4

Perhaps you’ve forgotten about your thread from a day ago? A strange phenomenon with this maximize problem

5

Thanks for your reply, but I think they are different, I will try it in other ways.

6

The message I conveyed is the same even if the code is not identical.

7

Okay, thanks for your help.