Testing and Evaluating the Single Objective Intelligent Evolutionary Algorithm through a Graphic Interface

Abstract

The human evolutionary model is an intelligent global optimization method conceived to perform single and multiple objective optimization, this general method is still in development, especially the multi objective (MO) part is being improved. The single objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example differential evolution (DE), particle swarm optimizer, and others, we called this part single objective intelligent evolutionary algorithm (SO-IEA). The SO-IEA uses mediative fuzzy logic (MFL) for handling doubtful and contradictory information from experts to calculate the appropriated amount of individuals to create and/or to eliminate. MFL is an extension of traditional fuzzy logic and includes intuitionistic fuzzy logic (IFL) in the Atanassov sense. In this work, we are presenting the algorithm's architecture, experimental results, and a graphical interface that will help to handle the required parameters to use the SO-IEA.