General structure-based classification of Optimization Algorithms for an objective comparison

The aim of this work is to introduce an effective tool in order to help the EM designer to select the best optimization algorithm through an easy-to-manage classification of Evolutionary Algorithms. In fact, choosing the best tool for an application could be really di cult, especially for a user not aware of optimization theory. Here we propose a general analysis for EAs, highlighting their block-structure and classifying them through some objective (non-qualitative) parameters.