I recently working on a non-convex optimization problem, and I have used Bayesian Optimization as a method to solve this problem. And it didn't show good convergence. (Is Bayesian Optimization is an effective way to solve this problem?)
Anyone can help me to see if there're other efficient ways to solve the non-convex optimization problem? I'm using python, so, could anyone show me some package in python that can do it?
Thank you!
There’s way too little information about your problem to suggest a solution. How many parameters do you have in your objective function? Do you have analytical gradients available? Is your objective function expensive to evaluate or very fast? Do you have bound constraints? Linear and/or nonlinear constraints? Do you care about trying to find a global optimum or are you happy with a good enough local minimum/maximum? Any reason why you chose Bayesian optimization to start with?