IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v140y2002i1p12-23.html
   My bibliography  Save this article

A new multiobjective evolutionary algorithm

Author

Listed:
  • Sarker, Ruhul
  • Liang, Ko-Hsin
  • Newton, Charles

Abstract

No abstract is available for this item.

Suggested Citation

  • Sarker, Ruhul & Liang, Ko-Hsin & Newton, Charles, 2002. "A new multiobjective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 140(1), pages 12-23, July.
  • Handle: RePEc:eee:ejores:v:140:y:2002:i:1:p:12-23
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(01)00190-4
    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.

    Citations

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


    Cited by:

    1. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    2. Quan, Gang & Greenwood, Garrison W. & Liu, Donglin & Hu, Sharon, 2007. "Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1969-1984, March.
    3. Elaoud, Semya & Loukil, Taicir & Teghem, Jacques, 2007. "The Pareto fitness genetic algorithm: Test function study," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1703-1719, March.
    4. Jacinto Martín & Concha Bielza & David Ríos Insua, 2005. "Approximating nondominated sets in continuous multiobjective optimization problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 469-480, August.
    5. Choobineh, F. Fred & Mohebbi, Esmail & Khoo, Hansen, 2006. "A multi-objective tabu search for a single-machine scheduling problem with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 175(1), pages 318-337, November.
    6. Wang, Yujia & Yang, Yupu, 2010. "Particle swarm with equilibrium strategy of selection for multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 200(1), pages 187-197, January.
    7. Koutras, V.P. & Platis, A.N. & Gravvanis, G.A., 2009. "Optimal server resource reservation policies for priority classes of users under cyclic non-homogeneous markov modeling," European Journal of Operational Research, Elsevier, vol. 198(2), pages 545-556, October.
    8. Chen, Min-Rong & Lu, Yong-Zai, 2008. "A novel elitist multiobjective optimization algorithm: Multiobjective extremal optimization," European Journal of Operational Research, Elsevier, vol. 188(3), pages 637-651, August.
    9. Kumar, Ranjan & Izui, Kazuhiro & Yoshimura, Masataka & Nishiwaki, Shinji, 2009. "Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 891-904.
    10. Galinina Anna & Burceva Olga & Parshutin Sergei, 2012. "The Optimization of COCOMO Model Coefficients Using Genetic Algorithms," Information Technology and Management Science, Sciendo, vol. 15(1), pages 45-51, December.
    11. Shyamal Gondkar & Sivakumar Sreeramagiri & Edwin Zondervan, 2012. "Methodology for Assessment and Optimization of Industrial Eco-Systems," Challenges, MDPI, vol. 3(1), pages 1-21, June.
    12. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    13. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    14. Tan, K.C. & Goh, C.K. & Yang, Y.J. & Lee, T.H., 2006. "Evolving better population distribution and exploration in evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 171(2), pages 463-495, June.

    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:140:y:2002:i:1:p:12-23. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.