Guided Randomness in Optimization

The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated. Source-codes used for the examples are also presented, this allows a reflection on the "superfluous chance," succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.