IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i5p703-d1347657.html
   My bibliography  Save this article

An Improved Discrete Bat Algorithm for Multi-Objective Partial Parallel Disassembly Line Balancing Problem

Author

Listed:
  • Qi Zhang

    (College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China)

  • Yang Xing

    (College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China)

  • Man Yao

    (School of Basic Medicine, He University, Shenyang 110163, China)

  • Jiacun Wang

    (Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ 07764, USA)

  • Xiwang Guo

    (College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China)

  • Shujin Qin

    (College of Economics and Management, Shangqiu Normal University, Shangqiu 476000, China)

  • Liang Qi

    (Department of Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China)

  • Fuguang Huang

    (College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China)

Abstract

Product disassembly is an effective means of waste recycling and reutilization that has received much attention recently. In terms of disassembly efficiency, the number of disassembly skills possessed by workers plays a crucial role in improving disassembly efficiency. Therefore, in order to effectively and reasonably disassemble discarded products, this paper proposes a partial parallel disassembly line balancing problem (PP-DLBP) that takes into account the number of worker skills. In this paper, the disassembly tasks and the disassembly relationships between components are described using AND–OR graphs. In this paper, a multi-objective optimization model is established aiming to maximize the net profit of disassembly and minimize the number of skills for the workers. Based on the bat algorithm (BA), we propose an improved discrete bat algorithm (IDBA), which involves designing adaptive composite optimization operators to replace the original continuous formula expressions and applying them to solve the PP-DLBP. To demonstrate the advantages of IDBA, we compares it with NSGA-II, NSGA-III, SPEA-II, ESPEA, and MOEA/D. Experimental results show that IDBA outperforms the other five algorithms in real disassembly cases and exhibits high efficiency.

Suggested Citation

  • Qi Zhang & Yang Xing & Man Yao & Jiacun Wang & Xiwang Guo & Shujin Qin & Liang Qi & Fuguang Huang, 2024. "An Improved Discrete Bat Algorithm for Multi-Objective Partial Parallel Disassembly Line Balancing Problem," Mathematics, MDPI, vol. 12(5), pages 1-22, February.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:703-:d:1347657
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/5/703/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/5/703/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ali Koc & Ihsan Sabuncuoglu & Erdal Erel, 2009. "Two exact formulations for disassembly line balancing problems with task precedence diagram construction using an AND/OR graph," IISE Transactions, Taylor & Francis Journals, vol. 41(10), pages 866-881.
    2. Mohand Lounes Bentaha & Alexandre Dolgui & Olga Battaïa & Robert J. Riggs & Jack Hu, 2018. "Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 56(24), pages 7220-7242, December.
    3. Lixia Zhu & Zeqiang Zhang & Yi Wang, 2018. "A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(24), pages 7354-7374, December.
    Full references (including those not matched with items on IDEAS)

    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. Junkai He & Feng Chu & Feifeng Zheng & Ming Liu, 2021. "A green-oriented bi-objective disassembly line balancing problem with stochastic task processing times," Annals of Operations Research, Springer, vol. 296(1), pages 71-93, January.
    2. Fang, Yilin & Liu, Quan & Li, Miqing & Laili, Yuanjun & Pham, Duc Truong, 2019. "Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations," European Journal of Operational Research, Elsevier, vol. 276(1), pages 160-174.
    3. Lixia Zhu & Zeqiang Zhang & Yi Wang & Ning Cai, 2020. "On the end-of-life state oriented multi-objective disassembly line balancing problem," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1403-1428, August.
    4. Ömer Faruk Yılmaz & Büşra Yazıcı, 2022. "Tactical level strategies for multi-objective disassembly line balancing problem with multi-manned stations: an optimization model and solution approaches," Annals of Operations Research, Springer, vol. 319(2), pages 1793-1843, December.
    5. Peng Hu & Feng Chu & Yunfei Fang & Peng Wu, 2022. "Novel distribution-free model and method for stochastic disassembly line balancing with limited distributional information," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1423-1446, July.
    6. Bentaha, Mohand-Lounes & Voisin, Alexandre & Marangé, Pascale, 2020. "A decision tool for disassembly process planning under end-of-life product quality," International Journal of Production Economics, Elsevier, vol. 219(C), pages 386-401.
    7. Tao Yin & Yuanzhi Wang & Shixi Cai & Yuxun Zhang & Jianyu Long, 2024. "Unified Modeling and Multi-Objective Optimization for Disassembly Line Balancing with Distinct Station Configurations," Mathematics, MDPI, vol. 12(17), pages 1-24, September.
    8. Liang, Wei & Zhang, Zeqiang & Yin, Tao & Zhang, Yu & Wu, Tengfei, 2023. "Modelling and optimisation of energy consumption and profit-oriented multi-parallel partial disassembly line balancing problem," International Journal of Production Economics, Elsevier, vol. 262(C).
    9. Jianhua Cao & Xuhui Xia & Lei Wang & Zelin Zhang & Xiang Liu, 2019. "A Novel Multi-Efficiency Optimization Method for Disassembly Line Balancing Problem," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    10. 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).
    11. Wanlin Yang & Zixiang Li & Chenyu Zheng & Zikai Zhang & Liping Zhang & Qiuhua Tang, 2024. "Multi-Objective Optimization for a Partial Disassembly Line Balancing Problem Considering Profit and Carbon Emission," Mathematics, MDPI, vol. 12(8), pages 1-19, April.
    12. Yusha Zhou & Xiuping Guo & Dong Li, 2022. "A dynamic programming approach to a multi-objective disassembly line balancing problem," Annals of Operations Research, Springer, vol. 311(2), pages 921-944, April.
    13. Zepeng Chen & Lin Li & Xiaojing Chu & Fengfu Yin & Huaqing Li, 2024. "Multi-Objective Disassembly Depth Optimization for End-of-Life Smartphones Considering the Overall Safety of the Disassembly Process," Sustainability, MDPI, vol. 16(3), pages 1-23, January.
    14. Can B. Kalayci & Olcay Polat & Surendra M. Gupta, 2016. "A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem," Annals of Operations Research, Springer, vol. 242(2), pages 321-354, July.
    15. Bentaha, Mohand Lounes & Battaïa, Olga & Dolgui, Alexandre & Hu, S. Jack, 2015. "Second order conic approximation for disassembly line design with joint probabilistic constraints," European Journal of Operational Research, Elsevier, vol. 247(3), pages 957-967.
    16. Süleyman Mete & Faruk Serin & Zeynel Abidin Çil & Erkan Çelik & Eren Özceylan, 2023. "A comparative analysis of meta-heuristic methods on disassembly line balancing problem with stochastic time," Annals of Operations Research, Springer, vol. 321(1), pages 371-408, February.
    17. Yicong Gao & Shanhe Lou & Hao Zheng & Jianrong Tan, 2023. "A data-driven method of selective disassembly planning at end-of-life under uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 565-585, February.
    18. Wei Meng & Xiufen Zhang, 2020. "Optimization of Remanufacturing Disassembly Line Balance Considering Multiple Failures and Material Hazards," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
    19. Devika Kannan & Kiran Garg & P. C. Jha & Ali Diabat, 2017. "Integrating disassembly line balancing in the planning of a reverse logistics network from the perspective of a third party provider," Annals of Operations Research, Springer, vol. 253(1), pages 353-376, June.
    20. He, Junkai & Chu, Feng & Dolgui, Alexandre & Anjos, Miguel F., 2024. "Multi-objective disassembly line balancing and related supply chain management problems under uncertainty: Review and future trends," International Journal of Production Economics, Elsevier, vol. 272(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:gam:jmathe:v:12:y:2024:i:5:p:703-:d:1347657. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.