IDEAS home Printed from https://ideas.repec.org/a/taf/tjrtxx/v9y2021i3p290-309.html
   My bibliography  Save this article

Surrogate-assisted multi-objective optimization of the dynamic response of a freight wagon fitted with three-piece bogies

Author

Listed:
  • Manish Pandey
  • Rommel G. Regis
  • Rituparna Datta
  • Bishakh Bhattacharya

Abstract

The multi-objective optimization problem of the dynamic response of a freight wagon fitted with three-piece bogies is a challenging task due to interdependencies between the decision variables, conflicts between the objective functions and computationally expensive rail vehicle dynamic simulations. In this article, a novel approach of multi-objective optimization of the dynamic performance of a freight wagon fitted with three-piece bogies is presented. Surrogate modelling using radial basis function (RBF) ensembles have been used to model the five objective functions representing the dynamic performance of the freight wagon. Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) has been applied to optimize the objective functions formed using the surrogate models. Finally, to choose specific solutions from the identified Pareto fronts, the minimization of a weighted combination of the surrogate objective functions is solved for six combinations of weights. The weighted optimized solutions show significant improvements over the existing solution.

Suggested Citation

  • Manish Pandey & Rommel G. Regis & Rituparna Datta & Bishakh Bhattacharya, 2021. "Surrogate-assisted multi-objective optimization of the dynamic response of a freight wagon fitted with three-piece bogies," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 9(3), pages 290-309, May.
  • Handle: RePEc:taf:tjrtxx:v:9:y:2021:i:3:p:290-309
    DOI: 10.1080/23248378.2020.1792808
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23248378.2020.1792808
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23248378.2020.1792808?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.

    Citations

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


    Cited by:

    1. Shuai Zhang & Weizhen Wei & Xiaoliang Chen & Liyou Xu & Yuntao Cao, 2022. "Vibration Performance Analysis and Multi-Objective Optimization Design of a Tractor Scissor Seat Suspension System," Agriculture, MDPI, vol. 13(1), pages 1-28, December.

    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:taf:tjrtxx:v:9:y:2021:i:3:p:290-309. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjrt20 .

    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.