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Rigorous Runtime Analysis of Swarm Intelligence Algorithms – An Overview

  • Carsten Witt
Part of the Studies in Computational Intelligence book series (SCI, volume 242)

Summary

The theoretical runtime analysis of randomized search heuristics is an emerging research area where many results have been obtained in recent years. Most of these studies deal with evolutionary algorithms rather than swarm intelligence approaches such as ant colony optimization and particle swarm optimization. Despite the overwhelming practical success of swarm intelligence, the first runtime analyses of such approaches date only from 2006. Since then, however, significant progress has been made in analyzing the runtime of simple ACO and PSO variants. The aim of this chapter is to give an overview on existing studies in this area. Moreover, it is elaborated what direction the theory of swarm intelligence is likely to take, and the vision of a unified theory of randomized search heuristics is discussed.

Keywords

Local Search Minimum Span Tree Swarm Intelligence Construction Graph Construction Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Carsten Witt
    • 1
  1. 1.DTU Informatics, Technical University of DenmarkLyngbyDenmark

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