Can anyone recommend some books about global optimization? I will have to make a work about that topic despite I don't know exactly the title yet, so any level and approach is welcomed.
Update [Jan 2022]: I was finally given new information about the topic. The next two linked papers are suposed to show a more specific approach about the kind of references I will need.
1-. Introduction to global optimization - Liberti
2-. Optimización global de funciones no diferenciables (spanish text)
In [2-.], for those who don't know spanish, it is shown an iterative method to search global minima for (not globally) differentiable, lipschitz functions.
The first text however, covers a wide range in nonlinear optimization: mixed-integer problems, Karush-Kuhn-Tucker conditions, two-phases algorithms, deterministic spatial Brunch&Bound method, convex relaxation, stochastic global multistart algorithms (Sobol), not necessary convex spaces or functions...
As before, any book recommendation covering those terms or working about related nonlinear programming is welcome.
Thanks.
The best answers probably depend more on what you are looking to learn. But, two of my favorite general textbooks on optimization are: