IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v30y2019i3d10.1007_s10845-017-1328-0.html
   My bibliography  Save this article

An improved backtracking search algorithm for casting heat treatment charge plan problem

Author

Listed:
  • Jianxin Zhou

    (Huazhong University of Science and Technology)

  • Hu Ye

    (Huazhong University of Science and Technology)

  • Xiaoyuan Ji

    (Huazhong University of Science and Technology)

  • Weilin Deng

    (Huazhong University of Science and Technology)

Abstract

This study investigates the optimization of the charge plan in casting heat treatment. The optimization problem is formulated as a 0–1 integer programming model aiming at maximizing the utilization of the furnaces, minimizing the holding temperature differences and the overall delivery deadline of castings in a furnace. To approach the mathematical model, a two-steps solution methodology is designed. First, the feasible casting candidate sets are generated in consideration of the holding temperature and cooling mode constraints. Then, an improved backtracking search algorithm (IBSA) is proposed to obtain optimal charge plan for each feasible candidate set. The best one among the optimal charge plans obtained by IBSA is selected as the final charge plan. In IBSA, a mapping mechanism is applied to make original backtracking search algorithm (BSA) suitable to discrete problems. Improvements that consist of the modification of historical population updating mechanism, the hybrid of mutation and crossover strategy of difference evaluation algorithm, a greedy local search algorithm and the re-initialization operator are also made to enhance the exploitation and exploration ability of IBSA. The comparisons of simulation experiments demonstrate the effectiveness of the proposed model and the performance of the proposed algorithm.

Suggested Citation

  • Jianxin Zhou & Hu Ye & Xiaoyuan Ji & Weilin Deng, 2019. "An improved backtracking search algorithm for casting heat treatment charge plan problem," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1335-1350, March.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1328-0
    DOI: 10.1007/s10845-017-1328-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-017-1328-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-017-1328-0?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. Hager Triki & Ahmed Mellouli & Faouzi Masmoudi, 2017. "A multi-objective genetic algorithm for assembly line resource assignment and balancing problem of type 2 (ALRABP-2)," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 371-385, February.
    2. dos Santos-Meza, Elisangela & Oliveira dos Santos, Maristela & Nereu Arenales, Marcos, 2002. "A lot-sizing problem in an automated foundry," European Journal of Operational Research, Elsevier, vol. 139(3), pages 490-500, June.
    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. Yiying Zhang & Aining Chi, 2023. "Group teaching optimization algorithm with information sharing for numerical optimization and engineering optimization," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 1547-1571, 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. Wei, Wenchao & Guimarães, Luis & Amorim, Pedro & Almada-Lobo, Bernardo, 2017. "Tactical production and distribution planning with dependency issues on the production process," Omega, Elsevier, vol. 67(C), pages 99-114.
    2. V S Tonaki & F M B Toledo, 2010. "An approach for solving the lot-sizing problem of a market-driven foundry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 108-114, January.
    3. Jans, R.F., 2006. "Solving Lotsizing Problems on Parallel Identical Machines Using Symmetry Breaking Constraints," ERIM Report Series Research in Management ERS-2006-051-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. 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).
    5. Raf Jans, 2009. "Solving Lot-Sizing Problems on Parallel Identical Machines Using Symmetry-Breaking Constraints," INFORMS Journal on Computing, INFORMS, vol. 21(1), pages 123-136, February.
    6. Boysen, Nils & Schulze, Philipp & Scholl, Armin, 2022. "Assembly line balancing: What happened in the last fifteen years?," European Journal of Operational Research, Elsevier, vol. 301(3), pages 797-814.

    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:joinma:v:30:y:2019:i:3:d:10.1007_s10845-017-1328-0. 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.