• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Ant Colony System: A cooperative learning approach to the traveling salesman problem (1997)

Cached

  • Download as a PDF

Download Links

  • [code.ulb.ac.be]
  • [www.inf.utfsm.cl]
  • [read.pudn.com]
  • [ftp.idsia.ch]
  • [www.idsia.ch]
  • [www.idsia.ch]
  • [vmk.ugatu.ac.ru]
  • [dsp.jpl.nasa.gov]
  • [faculty.washington.edu]
  • [staff.washington.edu]
  • [www.comp.nus.edu.sg]
  • [www-igm.univ-mlv.fr]
  • [www-igm.univ-mlv.fr]
  • [www.ppgia.pucpr.br]
  • [sci2s.ugr.es]
  • [iridia.ulb.ac.be]
  • [iridia.ulb.ac.be]
  • [ftp.idsia.ch]
  • [nuyoo.utm.mx]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Marco Dorigo , Luca Maria Gambardella
Venue:IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
Citations:1026 - 50 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@ARTICLE{Dorigo97antcolony,
    author = {Marco Dorigo and Luca Maria Gambardella},
    title = {Ant Colony System: A cooperative learning approach to the traveling salesman problem},
    journal = {IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION},
    year = {1997}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants cooperate to find good solutions to TSP’s. Ants cooperate using an indirect form of communication mediated by a pheromone they deposit on the edges of the TSP graph while building solutions. We study the ACS by running experiments to understand its operation. The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and we conclude comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSP’s.

Keyphrases

salesman problem    ant colony system    cooperative learning approach    simulated annealing    good solution    distributed algorithm    local search procedure    performing algorithm    indirect form    tsp graph    evolutionary computation    nature-inspired algorithm    asymmetric tsp   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University