The result of CVX solver is not the best point

[Zc_Lin]

supposing the variable to optimize is V, I did a Taylor expansion to make the problem convex.

if i do the Taylor expansion at V_0, obviously V_0 is a feasible resolution to my problem. But sometimes, after cvx, the V_{new} I got caused a worse result than V_0.

Could this be due to accuracy errors, or does it mean that my code has something wrongs?

[Mark_L_Stone]

The result obtained using the SeDuMi solver is inaccurate. The optimal solution is not as good as before the optimization.

Unsafeguarded (no line search or trust region)Successive Convex Approximation (SCA) or generally, alternating variables optimization are unreliable. It might not descend (for minimization problem), i.e., iterates could get worse. It might not converge to anything; and if it does converge, it might not be to a local optimum of the original problem, let alone a global optimum. The solution of successive iterations, and therefore subproblem inputs, can become wilder and wilder, until at some point …