When considering noisy fitness functions for some CPU-time consuming applications, a trade-off problem arise: how to reduce
the influence of the noise while not increasing too much computation time. In this paper, we propose and experiment some new
strategies based on an exploitation of historical information on the algorithm evolution, and a non-generational evolutionary
algorithm.