skip to main content
10.1145/2001858.2001928acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
poster

Comparison of cooperative, multiobjective cooperative and classical evolutionary algorithms for global supply chain optimisation

Published: 12 July 2011 Publication History

Abstract

This paper discusses global optimisation from a business perspective in the context of the supply chain operations. A two-silo supply chain was built for experimentation and three approaches were used for global optimisation: a classical evolutionary approach, a cooperative coevolutionary approach and a cooperative coevolutionary approach with non-dominated partner selection. The second approach produced higher quality solutions due to its use of communication between silos.

References

[1]
N. Christofides, A. Mingozzi, and P. Toth. The vehicle routing problem. Combinatorial Optimization, page 431--448, 1979.
[2]
M. Ibrahimov, A. Mohais, S. Schellenberg, and Z. Michalewicz. Comparison of different evolutionary algorithms for global supply chain optimisation and parameter analysis. In 2011 IEEE Congress on Evolutionary Computation, 2011.
[3]
M. Ibrahimov, N. Wagner, A. Mohais, S. Schellenberg, and Z. Michalewicz. Comparison of cooperative and classical evolutionary algorithms for global supply chain optimisation. In IEEE World Congress on Computational Intelligence, 2010.
[4]
E. Taillard. Benchmarks for basic scheduling problems. European Journal of Operational Research, 64(2):278--285, January 1993.

Cited By

View all
  • (2011)Comparison of different evolutionary algorithms for global supply chain optimisation and parameter analysis2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949915(2407-2414)Online publication date: Jun-2011

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
July 2011
1548 pages
ISBN:9781450306904
DOI:10.1145/2001858

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2011

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. cooperative coevolution
  2. evolutionary algorithms
  3. global optimisation
  4. supply chain

Qualifiers

  • Poster

Conference

GECCO '11
Sponsor:

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 13 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2011)Comparison of different evolutionary algorithms for global supply chain optimisation and parameter analysis2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949915(2407-2414)Online publication date: Jun-2011

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media