The Impact of Complex Network Models to EDAs

Abstract

The study conducted in this paper is mainly driven by the topological characteristics of the structures that the interactions among the variables of the problems provide. Taking as reference the emergent field of complex networks, we generate a wide spectrum of networks that will serve as problem structures. Then, the impact that the topological characteristics of those networks have, both in the hardness of the optimization problem and in the behavior of the EDA, is analyzed. This reveals a relationship among the topology of the problem structure, the difficulty of the problems and the dependences that the algorithm needs to learn in order to solve the problems.