IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1299-d1091097.html
   My bibliography  Save this article

Multi-Objective Optimization for Mixed-Model Two-Sided Disassembly Line Balancing Problem Considering Partial Destructive Mode

Author

Listed:
  • Bao Chao

    (The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Peng Liang

    (The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Chaoyong Zhang

    (The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Hongfei Guo

    (School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China)

Abstract

Large-volume waste products, such as refrigerators and automobiles, not only consume resources but also pollute the environment easily. A two-sided disassembly line is the most effective method to deal with large-volume waste products. How to reduce disassembly costs while increasing profit has emerged as an important and challenging research topic. Existing studies ignore the diversity of waste products as well as uncertain factors such as corrosion and deformation of parts, which is inconsistent with the actual disassembly scenario. In this paper, a partial destructive mode is introduced into the mixed-model two-sided disassembly line balancing problem, and the mathematical model of the problem is established. The model seeks to comprehensively optimize the number of workstations, the smoothness index, and the profit. In order to obtain a high-quality disassembly scheme, an improved non-dominated sorting genetic algorithm-II (NSGA-II) is proposed. The proposed model and algorithm are then applied to an automobile disassembly line as an engineering illustration. The disassembly scheme analysis demonstrates that the partial destructive mode can raise the profit of a mixed-model two-sided disassembly line. This research has significant application potential in the recycling of large-volume products.

Suggested Citation

  • Bao Chao & Peng Liang & Chaoyong Zhang & Hongfei Guo, 2023. "Multi-Objective Optimization for Mixed-Model Two-Sided Disassembly Line Balancing Problem Considering Partial Destructive Mode," Mathematics, MDPI, vol. 11(6), pages 1-17, March.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1299-:d:1091097
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1299/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/6/1299/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rehman, Shafique Ur & Kraus, Sascha & Shah, Syed Asim & Khanin, Dmitry & Mahto, Raj V., 2021. "Analyzing the relationship between green innovation and environmental performance in large manufacturing firms," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Mohand Lounes Bentaha & Olga Battaïa & Alexandre Dolgui, 2015. "An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1807-1818, March.
    3. Yılmaz Delice & Emel Kızılkaya Aydoğan & Uğur Özcan & Mehmet Sıtkı İlkay, 2017. "A modified particle swarm optimization algorithm to mixed-model two-sided assembly line balancing," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 23-36, January.
    4. J. L. C. Macaskill, 1972. "Production-Line Balances for Mixed-Model Lines," Management Science, INFORMS, vol. 19(4-Part-1), pages 423-434, December.
    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. 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).

    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. 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).
    2. Joseph I. Uduji & Elda N. Okolo-Obasi, 2022. "Gender Sensitive Responses to Climate Change in Nigeria: The Role of Multinationals’ Corporate Social Responsibility in Oil Host Communities," Working Papers 22/041, European Xtramile Centre of African Studies (EXCAS).
    3. Diefenbach, Johannes & Stolletz, Raik, 2022. "Stochastic assembly line balancing: General bounds and reliability-based branch-and-bound algorithm," European Journal of Operational Research, Elsevier, vol. 302(2), pages 589-605.
    4. Karabati, Selcuk & Sayin, Serpil, 2003. "Assembly line balancing in a mixed-model sequencing environment with synchronous transfers," European Journal of Operational Research, Elsevier, vol. 149(2), pages 417-429, September.
    5. Alisher Khamdamov & Zhiwei Tang & Muhammad Ali Hussain, 2023. "Unpacking Parallel Mediation Processes between Green HRM Practices and Sustainable Environmental Performance: Evidence from Uzbekistan," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    6. Xuhui Xia & Wei Liu & Zelin Zhang & Lei Wang & Jianhua Cao & Xiang Liu, 2019. "A Balancing Method of Mixed-model Disassembly Line in Random Working Environment," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    7. Xinwei Li & Wenjuan Zeng & Mao Xu, 2022. "The Moderating Role of IT Capability on Green Innovation and Ambidexterity: Towards a Corporate Sustainable Development," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    8. Muhammad Ibrahim & Rosli Mahmood, 2022. "Proactive Environmental Strategy and Environmental Performance of the Manufacturing SMEs of Karachi City in Pakistan: Role of Green Mindfulness as a DCV," Sustainability, MDPI, vol. 14(19), pages 1-14, September.
    9. Zhou, Chao & Lin, Feng, 2024. "Does global diversification promote or hinder green innovation? Evidence from Chinese multinational corporations," Technovation, Elsevier, vol. 129(C).
    10. Li, Zixiang & Kucukkoc, Ibrahim & Zhang, Zikai, 2020. "Branch, bound and remember algorithm for two-sided assembly line balancing problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 896-905.
    11. Marshall L. Fisher & Christopher D. Ittner, 1999. "The Impact of Product Variety on Automobile Assembly Operations: Empirical Evidence and Simulation Analysis," Management Science, INFORMS, vol. 45(6), pages 771-786, June.
    12. 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.
    13. Jin Zhu & Fei Huang, 2023. "Transformational Leadership, Organizational Innovation, and ESG Performance: Evidence from SMEs in China," Sustainability, MDPI, vol. 15(7), pages 1-23, March.
    14. Deng, Qiu Shi & Alvarado, Rafael & Cuesta, Lizeth & Tillaguango, Brayan & Murshed, Muntasir & Rehman, Abdul & Işık, Cem & López-Sánchez, Michelle, 2022. "Asymmetric impacts of foreign direct investment inflows, financial development, and social globalization on environmental pollution," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 236-251.
    15. Liang, Zhiying & Chen, Jian & Jiang, Dayang & Sun, Yunpeng, 2022. "Assessment of the spatial association network of green innovation: Role of energy resources in green recovery," Resources Policy, Elsevier, vol. 79(C).
    16. Meng Li & Zengrui Tian & Qian Liu & Yuzhong Lu, 2022. "Literature Review and Research Prospect on the Drivers and Effects of Green Innovation," Sustainability, MDPI, vol. 14(16), pages 1-23, August.
    17. 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).
    18. Li, Xin & Wu, Ming & Shi, Chunming & Chen, Yan, 2023. "Impacts of green credit policies and information asymmetry: From market perspective," Resources Policy, Elsevier, vol. 81(C).
    19. Mohammad Khajehzadeh & Suraparb Keawsawasvong & Moncef L. Nehdi, 2022. "Effective Hybrid Soft Computing Approach for Optimum Design of Shallow Foundations," Sustainability, MDPI, vol. 14(3), pages 1-20, February.
    20. Chu, Shaner, 2024. "Are women greener? Board gender diversity and corporate green technology innovation in China," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1001-1020.

    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:11:y:2023:i:6:p:1299-:d:1091097. 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.