IDEAS home Printed from https://ideas.repec.org/a/ids/ijsoma/v34y2019i1p33-47.html
   My bibliography  Save this article

Multi-objective assembly line balancing problem under uncertainty using genetic algorithm

Author

Listed:
  • Ferdous Sarwar

Abstract

This paper addresses the single-model multi-objective assembly line balancing (ALB) problem with fuzzy processing time. A fuzzy optimisation model is formulated for the problem. In the classical mathematical formulation of SALBP, the relevant data are considered deterministic. But, the data of the real world problems are imprecise, vague or uncertain. The input data should be estimated within uncertainty represented by a fuzzy number. The concept of fuzzy numbers is introduced to treat imprecise data, such as the processing time of each task. Due to the NP-hard nature of the ALB problem, heuristics are used to solve real life cases. In this paper, an efficient heuristic is proposed to solve the fuzzy multi-objective ALB problem. The proposed heuristic is based on genetic algorithm (GA) that is efficient to handle fuzzy job time through the evolution process. As the proposed algorithm can find out the optimum solution as a trade-off among several objectives, it outperforms the existing heuristics on several test cases. The proposed algorithm can be effectively used in the design phase of an assembly line.

Suggested Citation

  • Ferdous Sarwar, 2019. "Multi-objective assembly line balancing problem under uncertainty using genetic algorithm," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 34(1), pages 33-47.
    • Handle: RePEc:ids:ijsoma:v:34:y:2019:i:1:p:33-47
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=102030
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).

    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:ijsoma:v:34:y:2019:i:1:p:33-47. 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=150 .

    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.