Timeline for Robust black box function minimization with extremely expensive cost function
Current License: CC BY-SA 2.5
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| Sep 5, 2010 at 9:58 | comment | added | J. M. isn't a mathematician | To add to Gilead's comment: as enthusiastic as I usually am with downhill simplex, it's still best thought of as a "not-so-quick and dirty" method; for a problem with a lot of independent variables, it is worth one's while to see what structure is exploitable in his problem instead of mindlessly feeding it to an optimizer. | |
| Sep 5, 2010 at 3:37 | comment | added | Gilead | Yes, the "surprising" part is true. Despite advances in derivative-free methods, Nelder-Mead remains a competitive DFO algorithm, which is why it is still taught in many optimization courses. However, it is a heuristic and does not exploit the structure of the problem. Also, when a function is particularly expensive to evaluate, my view is that statistical methods (response surface modeling, particularly when projected into lower dimensional spaces) can help one avoid making unnecessary evaluations. Nelder-Mead was not designed with the goal of being parsimonious with function evaluations. | |
| Sep 5, 2010 at 1:57 | history | answered | umar | CC BY-SA 2.5 |