Use of the bio-inspired algorithms to find global minimum in force directed layout algorithms

Abstract

We present bio-inspired approach in a process of finding global minimum of an energetic function that is used in force directed layout algorithms. We have been faced with the issue of displaying large graphs. These graphs arise in the analysis of social networks with the need to view social relationships between entities. In order to find global minimum of an energetic function we employ two bio-inspired algorithms: Differential Evolution and Self- Organizing Migration Algorithm (SOMA). Differential evolution is inspired by crossbreeding of population whereas SOMA is inspired by migration of some species. In this article we will present basics of these algorithms, their results and comparison.