IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v176y2007i1p60-76.html
   My bibliography  Save this article

Integrated crossover rules in real coded genetic algorithms

Author

Listed:
  • Kaelo, P.
  • Ali, M.M.

Abstract

No abstract is available for this item.

Suggested Citation

  • Kaelo, P. & Ali, M.M., 2007. "Integrated crossover rules in real coded genetic algorithms," European Journal of Operational Research, Elsevier, vol. 176(1), pages 60-76, January.
    • Handle: RePEc:eee:ejores:v:176:y:2007:i:1:p:60-76
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(05)00704-6
    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. R. Yang & I. Douglas, 1998. "Simple Genetic Algorithm with Local Tuning: Efficient Global Optimizing Technique," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 449-465, August.
    2. Chelouah, Rachid & Siarry, Patrick, 2003. "Genetic and Nelder-Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions," European Journal of Operational Research, Elsevier, vol. 148(2), pages 335-348, July.
    3. Kaelo, P. & Ali, M.M., 2006. "A numerical study of some modified differential evolution algorithms," European Journal of Operational Research, Elsevier, vol. 169(3), pages 1176-1184, March.
    4. Chelouah, Rachid & Siarry, Patrick, 2005. "A hybrid method combining continuous tabu search and Nelder-Mead simplex algorithms for the global optimization of multiminima functions," European Journal of Operational Research, Elsevier, vol. 161(3), pages 636-654, March.
    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. Zou, Dexuan & Li, Steven & Kong, Xiangyong & Ouyang, Haibin & Li, Zongyan, 2019. "Solving the combined heat and power economic dispatch problems by an improved genetic algorithm and a new constraint handling strategy," Applied Energy, Elsevier, vol. 237(C), pages 646-670.
    2. Zhaowei Miao & Feng Yang & Ke Fu & Dongsheng Xu, 2012. "Transshipment service through crossdocks with both soft and hard time windows," Annals of Operations Research, Springer, vol. 192(1), pages 21-47, January.
    3. Chao Gong & Chunhui Xu & Ji Wang, 2018. "An Efficient Adaptive Real Coded Genetic Algorithm to Solve the Portfolio Choice Problem Under Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 227-252, June.
    4. Abdel-Rahman Hedar & Wael Deabes & Hesham H. Amin & Majid Almaraashi & Masao Fukushima, 2022. "Global sensing search for nonlinear global optimization," Journal of Global Optimization, Springer, vol. 82(4), pages 753-802, 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. Hvattum, Lars Magnus & Glover, Fred, 2009. "Finding local optima of high-dimensional functions using direct search methods," European Journal of Operational Research, Elsevier, vol. 195(1), pages 31-45, May.
    2. Morteza Ahandani & Mohammad-Taghi Vakil-Baghmisheh & Mohammad Talebi, 2014. "Hybridizing local search algorithms for global optimization," Computational Optimization and Applications, Springer, vol. 59(3), pages 725-748, December.
    3. Wang, Yong-Jun & Zhang, Jiang-She & Zhang, Gai-Ying, 2007. "A dynamic clustering based differential evolution algorithm for global optimization," European Journal of Operational Research, Elsevier, vol. 183(1), pages 56-73, November.
    4. Tammy Drezner & Zvi Drezner, 2019. "Cooperative Cover of Uniform Demand," Networks and Spatial Economics, Springer, vol. 19(3), pages 819-831, September.
    5. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.
    6. Weitao Sun & Yuan Dong, 2011. "Study of multiscale global optimization based on parameter space partition," Journal of Global Optimization, Springer, vol. 49(1), pages 149-172, January.
    7. M. Ali & W. Zhu, 2013. "A penalty function-based differential evolution algorithm for constrained global optimization," Computational Optimization and Applications, Springer, vol. 54(3), pages 707-739, April.
    8. Witanowski, Ł. & Klonowicz, P. & Lampart, P. & Suchocki, T. & Jędrzejewski, Ł. & Zaniewski, D. & Klimaszewski, P., 2020. "Optimization of an axial turbine for a small scale ORC waste heat recovery system," Energy, Elsevier, vol. 205(C).
    9. Niknam, Taher & Firouzi, Bahman Bahmani, 2009. "A practical algorithm for distribution state estimation including renewable energy sources," Renewable Energy, Elsevier, vol. 34(11), pages 2309-2316.
    10. Andreas C. Nearchou & Sotiris L. Omirou, 2024. "Self-Adaptive Biased Differential Evolution for Scheduling Against Common Due Dates," SN Operations Research Forum, Springer, vol. 5(2), pages 1-29, June.
    11. A Corominas & R Pastor, 2011. "Designing greedy algorithms for the flow-shop problem by means of Empirically Adjusted Greedy Heuristics (EAGH)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1704-1710, September.
    12. Tammy Drezner & Zvi Drezner & Atsuo Suzuki, 2019. "A cover based competitive facility location model with continuous demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(7), pages 565-581, October.
    13. Liou, Cheng-Dar & Hsieh, Yi-Chih, 2015. "A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 258-267.
    14. Maysam Safe & Seyed Khazraee & Payam Setoodeh & Abdolhosein Jahanmiri, 2013. "Model reduction and optimization of a reactive dividing wall batch distillation column inspired by response surface methodology and differential evolution," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 19(1), pages 29-50.
    15. Georgieva, A. & Jordanov, I., 2009. "Global optimization based on novel heuristics, low-discrepancy sequences and genetic algorithms," European Journal of Operational Research, Elsevier, vol. 196(2), pages 413-422, July.
    16. Jourdan, L. & Basseur, M. & Talbi, E.-G., 2009. "Hybridizing exact methods and metaheuristics: A taxonomy," European Journal of Operational Research, Elsevier, vol. 199(3), pages 620-629, December.
    17. Mortazavi, Amir & Alabdulkarem, Abdullah & Hwang, Yunho & Radermacher, Reinhard, 2016. "Development of a robust refrigerant mixture for liquefaction of highly uncertain natural gas compositions," Energy, Elsevier, vol. 113(C), pages 1042-1050.
    18. Mohsen Davoodi & Hamed Jafari Kaleybar & Morris Brenna & Dario Zaninelli, 2023. "Energy Management Systems for Smart Electric Railway Networks: A Methodological Review," Sustainability, MDPI, vol. 15(16), pages 1-35, August.
    19. Chao Gong & Chunhui Xu & Ji Wang, 2018. "An Efficient Adaptive Real Coded Genetic Algorithm to Solve the Portfolio Choice Problem Under Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 227-252, June.
    20. Gouvêa, Érica J.C. & Regis, Rommel G. & Soterroni, Aline C. & Scarabello, Marluce C. & Ramos, Fernando M., 2016. "Global optimization using q-gradients," European Journal of Operational Research, Elsevier, vol. 251(3), pages 727-738.

    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:176:y:2007:i:1:p:60-76. 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.