IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v181y2007i3p1670-1690.html
   My bibliography  Save this article

Working principles, behavior, and performance of MOEAs on MNK-landscapes

Author

Listed:
  • Aguirre, Hernan E.
  • Tanaka, Kiyoshi

Abstract

No abstract is available for this item.

Suggested Citation

  • Aguirre, Hernan E. & Tanaka, Kiyoshi, 2007. "Working principles, behavior, and performance of MOEAs on MNK-landscapes," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1670-1690, September.
  • Handle: RePEc:eee:ejores:v:181:y:2007:i:3:p:1670-1690
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(06)00545-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lee Altenberg, 1994. "Evolving Better Representations Through Selective Genome Growth," Working Papers 94-02-008, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Verel, Sébastien & Liefooghe, Arnaud & Jourdan, Laetitia & Dhaenens, Clarisse, 2013. "On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives," European Journal of Operational Research, Elsevier, vol. 227(2), pages 331-342.
    2. Madalina M. Drugan, 2019. "Random walk’s correlation function for multi-objective NK landscapes and quadratic assignment problem," Journal of Combinatorial Optimization, Springer, vol. 38(4), pages 1213-1262, November.
    3. Marcella S. R. Martins & Mohamed El Yafrani & Myriam Delgado & Ricardo Lüders & Roberto Santana & Hugo V. Siqueira & Huseyin G. Akcay & Belaïd Ahiod, 2021. "Analysis of Bayesian Network Learning Techniques for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: a case study on MNK Landscape," Journal of Heuristics, Springer, vol. 27(4), pages 549-573, August.
    4. Allmendinger, Richard & Handl, Julia & Knowles, Joshua, 2015. "Multiobjective optimization: When objectives exhibit non-uniform latencies," European Journal of Operational Research, Elsevier, vol. 243(2), pages 497-513.
    5. Derbel, Bilel & Humeau, Jérémie & Liefooghe, Arnaud & Verel, Sébastien, 2014. "Distributed localized bi-objective search," European Journal of Operational Research, Elsevier, vol. 239(3), pages 731-743.
    6. Mădălina M. Drugan, 2018. "Scaling-up many-objective combinatorial optimization with Cartesian products of scalarization functions," Journal of Heuristics, Springer, vol. 24(2), pages 135-172, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dario Blanco-Fernandez & Stephan Leitner & Alexandra Rausch, 2022. "Interactions between the individual and the group level in organizations: The case of learning and autonomous group adaptation," Papers 2203.09162, arXiv.org.
    2. Andreas Reinstaller & Werner Hölzl, 2004. "Complementarity constraints and induced innovation: some evidence from the first IT regime," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 6, Edward Elgar Publishing.
    3. Murmann, Johann Peter & Frenken, Koen, 2006. "Toward a systematic framework for research on dominant designs, technological innovations, and industrial change," Research Policy, Elsevier, vol. 35(7), pages 925-952, September.
    4. Koen Frenken, 2006. "Technological innovation and complexity theory," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 15(2), pages 137-155.
    5. Karén Hovhannissian & Marco Valente, 2004. "Modeling Directed Local Search Strategies on Technology Landscapes: Depth and Breadth," ROCK Working Papers 028, Department of Computer and Management Sciences, University of Trento, Italy, revised 17 Jun 2008.
    6. Valente Houhannisian, 2004. "Modeling Directod Local Search Strategies on Technology Landscapes and Breadth," Quaderni DISA 091, Department of Computer and Management Sciences, University of Trento, Italy, revised 17 Jun 2008.
    7. Karén Hovhannisian & Marco Valente, 2005. "Modeling Directed Local Search Strategies on Technology," Computational Economics 0507001, University Library of Munich, Germany.
    8. Ma, Tieju & Nakamori, Yoshiteru, 2005. "Agent-based modeling on technological innovation as an evolutionary process," European Journal of Operational Research, Elsevier, vol. 166(3), pages 741-755, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:181:y:2007:i:3:p:1670-1690. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.