Surrogate Optimisation

When the optimisation problem gives rise to objective functions which are prohibitively expensive to evaluate (like in aerodynamic simulation), a single optimisation case can take many minutes, hours, or even days to complete and often the whole optimisation process become infeasible. Optimisation methods based on surrogate models, have been successfully employed to tackle expensive objective functions. An attractive way to reduce the search time of EAs when dealing with expensive objective function is to use a cheap approximation model, that can rank the population similarly as the original expensive evaluation function.

Project description

Calul d'interactions pales tourbillons

Computing and Electronic Engineering

Ahmed Kattan