European Centre for Living Technology

Ant Colony Optimization: A Successful Stochastic Local Search Technique

by

Dr. Thomas Stuetzle, Universite' Libre de Bruxelles

Abstract:

Stochastic local search (SLS) algorithms such as simulated annealing, iterated local search, ant colony optimization or evolutionary algorithms are amongst the most prominent and successful techniques for solving computationally hard problems in many areas of Computer Science, Bioinformatics and Operations Research.
In this talk we give a short overview of the field of SLS algorithms with a special emphasis on the main techniques available in SLS. We then focus on one specific SLS method, Ant Colony Optimization (ACO).
In the talk we review shortly the inspiring source of ACO and the development of the main variants of ACO algorithms. We will then consider the most important recent developments. In particular, we will shortly review the main application areas of ACO, highlight recent developments on the algorithmic side including hybrids with other algorithmic techniques, and give an overview of the current status of theoretical results on ACO algorithms.