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Balancing Disassembly Line in Product Recovery to Promote the Coordinated Development of Economy and Environment

Author

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  • Jia Liu

    (School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China
    School of Management and Economics, Tianfu College of Southwestern University of Finance and Economics, Mianyang 621000, China)

  • Shuwei Wang

    (School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China
    School of Information and Technology, Tianfu College of Southwestern University of Finance and Economics, Mianyang 621000, China)

Abstract

For environmentally conscious and sustainable manufacturing, many more manufacturers are acting to recycle and remanufacture their post-consumed products. The most critical process of remanufacturing is disassembly, since it allows for the selective extraction of the valuable components and materials from returned products to reduce the waste disposal volume. It is, therefore, important to design and balance the disassembly line to work efficiently due to its vital role in effective resource usage and environmental protection. Considering the disassembly precedence relationships and sequence-dependent parts removal time increments, this paper presents an improved discrete artificial bee colony algorithm (DABC) for solving the sequence-dependent disassembly line balancing problem (SDDLBP). The performance of the proposed algorithm was tested against nine other approaches. Computational results evidently indicate the superior efficiency of the proposed algorithm for addressing the environmental and economic concerns while optimizing the multi-objective SDDLBP.

Suggested Citation

  • Jia Liu & Shuwei Wang, 2017. "Balancing Disassembly Line in Product Recovery to Promote the Coordinated Development of Economy and Environment," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:309-:d:90945
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    References listed on IDEAS

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    1. Andres, Carlos & Miralles, Cristobal & Pastor, Rafael, 2008. "Balancing and scheduling tasks in assembly lines with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1212-1223, June.
    2. Pan, Quan-Ke, 2016. "An effective co-evolutionary artificial bee colony algorithm for steelmaking-continuous casting scheduling," European Journal of Operational Research, Elsevier, vol. 250(3), pages 702-714.
    3. 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.
    4. 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.
    5. McGovern, Seamus M. & Gupta, Surendra M., 2007. "A balancing method and genetic algorithm for disassembly line balancing," European Journal of Operational Research, Elsevier, vol. 179(3), pages 692-708, June.
    6. Hamta, Nima & Fatemi Ghomi, S.M.T. & Jolai, F. & Akbarpour Shirazi, M., 2013. "A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect," International Journal of Production Economics, Elsevier, vol. 141(1), pages 99-111.
    7. Virginia Barba-Sánchez & Carlos Atienza-Sahuquillo, 2016. "Environmental Proactivity and Environmental and Economic Performance: Evidence from the Winery Sector," Sustainability, MDPI, vol. 8(10), pages 1-15, October.
    8. Szeto, W.Y. & Wu, Yongzhong & Ho, Sin C., 2011. "An artificial bee colony algorithm for the capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 215(1), pages 126-135, November.
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    Cited by:

    1. Junyong Liang & Shunsheng Guo & Yunfei Zhang & Wenfang Liu & Shengwen Zhou, 2021. "Energy-Efficient Optimization of Two-Sided Disassembly Line Balance Considering Parallel Operation and Uncertain Using Multiobjective Flatworm Algorithm," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    2. 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).
    3. Hao Liu & Lin Ma, 2020. "Spatial Pattern and Effects of Urban Coordinated Development in China’s Urbanization," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    4. 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.
    5. 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.
    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.

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