IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v50y2011i3p417-437.html
   My bibliography  Save this article

Massively parallel differential evolution—pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems

Author

Listed:
  • Weihang Zhu

Abstract

No abstract is available for this item.

Suggested Citation

  • Weihang Zhu, 2011. "Massively parallel differential evolution—pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems," Journal of Global Optimization, Springer, vol. 50(3), pages 417-437, July.
    • Handle: RePEc:spr:jglopt:v:50:y:2011:i:3:p:417-437
    DOI: 10.1007/s10898-010-9590-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10898-010-9590-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10898-010-9590-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Fan, Shu-Kai S. & Zahara, Erwie, 2007. "A hybrid simplex search and particle swarm optimization for unconstrained optimization," European Journal of Operational Research, Elsevier, vol. 181(2), pages 527-548, September.
    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. Ana Maria Ferreiro-Ferreiro & José Antonio García-Rodríguez & Luis A. Souto & Carlos Vázquez, 2020. "Efficient Model Points Selection in Insurance by Parallel Global Optimization Using Multi CPU and Multi GPU," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(1), pages 5-20, February.
    2. Konstantin Barkalov & Victor Gergel, 2016. "Parallel global optimization on GPU," Journal of Global Optimization, Springer, vol. 66(1), pages 3-20, September.
    3. Mathys Plessis & Andries Engelbrecht, 2013. "Differential evolution for dynamic environments with unknown numbers of optima," Journal of Global Optimization, Springer, vol. 55(1), pages 73-99, January.
    4. Ferreiro-Ferreiro, Ana M. & García-Rodríguez, José A. & Souto, Luis & Vázquez, Carlos, 2019. "Basin Hopping with synched multi L-BFGS local searches. Parallel implementation in multi-CPU and GPUs," Applied Mathematics and Computation, Elsevier, vol. 356(C), pages 282-298.
    5. Jinlong Yuan & Jun Xie & Honglei Xu & Enmin Feng & Zhilong Xiu, 2019. "Optimization for Nonlinear Uncertain Switched Stochastic Systems with Initial State Difference in Batch Culture Process," Complexity, Hindawi, vol. 2019, pages 1-15, February.

    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. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Syed Muhammad Arafat & Sher Afghan & Ahmad Hassan Kamal & Muhammad Asim & Muhammad Haider Khan & Muhammad Waqas Rafique & Uwe Naumann & Sajawal Gul Niazi &, 2020. "Optimization of a 660 MW e Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency," Energies, MDPI, vol. 13(21), pages 1-33, October.
    2. Jakubik, Johannes & Binding, Adrian & Feuerriegel, Stefan, 2021. "Directed particle swarm optimization with Gaussian-process-based function forecasting," European Journal of Operational Research, Elsevier, vol. 295(1), pages 157-169.
    3. Kuo, R.J. & Lee, Y.H. & Zulvia, Ferani E. & Tien, F.C., 2015. "Solving bi-level linear programming problem through hybrid of immune genetic algorithm and particle swarm optimization algorithm," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 1013-1026.
    4. Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2011. "A hybrid shuffled complex evolution approach with pattern search for unconstrained optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1901-1909.
    5. Witanowski, Łukasz & Ziółkowski, Paweł & Klonowicz, Piotr & Lampart, Piotr, 2023. "A hybrid approach to optimization of radial inflow turbine with principal component analysis," Energy, Elsevier, vol. 272(C).
    6. Paweł Ziółkowski & Łukasz Witanowski & Stanisław Głuch & Piotr Klonowicz & Michel Feidt & Aimad Koulali, 2024. "Example of Using Particle Swarm Optimization Algorithm with Nelder–Mead Method for Flow Improvement in Axial Last Stage of Gas–Steam Turbine," Energies, MDPI, vol. 17(12), pages 1-29, June.
    7. Shu-Kai S. Fan & Chih-Hung Jen, 2019. "An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization," Mathematics, MDPI, vol. 7(4), pages 1-16, April.
    8. 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.
    9. 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.
    10. Maryam Mousavi & Hwa Jen Yap & Siti Nurmaya Musa & Farzad Tahriri & Siti Zawiah Md Dawal, 2017. "Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-24, March.
    11. Jianfeng Liu & Nikolaos Ploskas & Nikolaos V. Sahinidis, 2019. "Tuning BARON using derivative-free optimization algorithms," Journal of Global Optimization, Springer, vol. 74(4), pages 611-637, August.
    12. Xiao, Yi & Liu, John J. & Hu, Yi & Wang, Yingfeng & Lai, Kin Keung & Wang, Shouyang, 2014. "A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 1-11.
    13. Khalid Abdulaziz Alnowibet & Salem Mahdi & Ahmad M. Alshamrani & Karam M. Sallam & Ali Wagdy Mohamed, 2022. "A Family of Hybrid Stochastic Conjugate Gradient Algorithms for Local and Global Minimization Problems," Mathematics, MDPI, vol. 10(19), pages 1-37, October.
    14. Xu, Meng & Droguett, Enrique López & Lins, Isis Didier & das Chagas Moura, Márcio, 2017. "On the q-Weibull distribution for reliability applications: An adaptive hybrid artificial bee colony algorithm for parameter estimation," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 93-105.
    15. Ferreiro, Ana M. & García-Rodríguez, José Antonio & Vázquez, Carlos & e Silva, E. Costa & Correia, A., 2019. "Parallel two-phase methods for global optimization on GPU," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 67-90.

    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:spr:jglopt:v:50:y:2011:i:3:p:417-437. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.