IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v54y2025i3p372-392.html

Aspiration level-based multi-objective quasi oppositional Jaya algorithm to solve multi-objective solid travelling salesman problem with carbon emission

Author

Listed:
  • Aaishwarya Bajaj
  • Jayesh M. Dhodiya

Abstract

The multi-objective solid travelling salesman problem (MOSTSP) is a complex optimisation problem as it employs multiple conveyances while travelling. In this paper, a newly developed aspiration level-based multi-objective quasi oppositional Jaya (AL-based MOQO Jaya) algorithm is used to tackle MOSTSP addressed within a crisp environment. A real-life example of Surat City is considered for 10 and 50 nodes, with five distinct objectives: cost, time, risk, distance, and carbon emission, with carbon-constrained. The obtained outcomes are compared with the results of the hybrid genetic algorithm (HGA) and the CPLEX optimisation tool. Remarkably, the AL-based MOQO Jaya algorithm exhibits significantly low computational time as compared to CPLEX and HGA. Furthermore, the performance of the algorithm is the study using coverage. The paper, concludes that the AL-based MOQO Jaya algorithm efficiently solves the MOSTSP, with effective output and provides alternative decision-making solutions to decision-makers.

Suggested Citation

  • Aaishwarya Bajaj & Jayesh M. Dhodiya, 2025. "Aspiration level-based multi-objective quasi oppositional Jaya algorithm to solve multi-objective solid travelling salesman problem with carbon emission," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 54(3), pages 372-392.
    • Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:372-392
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=149659
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:ids:ijores:v:54:y:2025:i:3:p:372-392. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=170 .

    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.