Multi-Objective Mixture-based Iterated Density Estimation Evolutionary Algorithms

Abstract

We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (M IDE A). The M IDE A algorithm is a probabilistic model building evolutionary algorithm that constructs at each generation a mixture of factorized probability distributions