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An optimisation support for the design of hybrid production lines including assembly and disassembly tasks

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  • Süleyman Mete
  • Zeynel Abidin Çil
  • Eren Özceylan
  • Kürşad Ağpak
  • Olga Battaïa

Abstract

The optimisation problems related to the assignment of tasks to workstations in assembly and disassembly lines have been largely discussed in the literature. They are known, respectively, as Assembly Line Balancing and Disassembly Line Balancing Problems. In this study, both types of task performed on the identical product are integrated in a common hybrid production system. Therefore, the logistic process is simplified and disassembly tasks can supply easier the assembly tasks with the required components. The considered production system has the layout of two parallel lines with common workstations. The product flow is conventional in the assembly line and reverse in the disassembly line. The paper provides a new mathematical model for designing such a hybrid system and an approximate approach based on ant colony optimisation for solving large-scale instances. The solution method is tested in a case study. The obtained results are compared with the solution provided by the design of two independent lines. The analysis of the results highlights the potential benefits of the hybrid production system.

Suggested Citation

  • Süleyman Mete & Zeynel Abidin Çil & Eren Özceylan & Kürşad Ağpak & Olga Battaïa, 2018. "An optimisation support for the design of hybrid production lines including assembly and disassembly tasks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(24), pages 7375-7389, December.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:24:p:7375-7389
    DOI: 10.1080/00207543.2018.1428774
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    Citations

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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. 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.
    3. Rapeepan Pitakaso & Kanchana Sethanan & Ganokgarn Jirasirilerd & Paulina Golinska-Dawson, 2023. "A novel variable neighborhood strategy adaptive search for SALBP-2 problem with a limit on the number of machine’s types," Annals of Operations Research, Springer, vol. 324(1), pages 1501-1525, May.
    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. 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.
    6. 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.

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