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A comparative analysis of meta-heuristic methods on disassembly line balancing problem with stochastic time

Author

Listed:
  • Süleyman Mete

    (Gaziantep University)

  • Faruk Serin

    (Mersin University)

  • Zeynel Abidin Çil

    (Izmir Democracy University)

  • Erkan Çelik

    (Istanbul University)

  • Eren Özceylan

    (Gaziantep University)

Abstract

The balancing of the disassembly line directly affects the productivity of the disassembly process. The disassembly line balancing (DLB) problem can be determined as assigning the tasks to serial workstations to optimize some performance measures like number of workstations, cycle time, removing hazardous parts earlier, etc. The aim of the paper is to develop an efficient heuristic algorithm to minimize the number of workstations under a pre-known cycle time. In this paper, a genetic algorithm (GA) and a constructive heuristic based on the Dijkstra algorithm is proposed to solve the DLB problem with stochastic task times that is caused by the nature of disassembly operation. The proposed algorithms are tested on benchmark problems and compared with the results of the piecewise-linear model (PLM) and simulated annealing (SA). The average relative percentage deviation is applied to transfer the obtained number of workstations. The results obtained by GA are clearly superior in all tests problem according to average relative percentage deviation. Moreover, the proposed constructive heuristic based on the Dijkstra algorithm is also superior to PLM and SA algorithm with respect to number of workstations and the computational times. The proposed approaches can be a very competitive and promising tool for further research in DLB literature and real cases in industries according to test results. Disassembly lines which need less time or number of workstations for balancing may be simply designed by the proposed techniques.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:321:y:2023:i:1:d:10.1007_s10479-022-04910-1
    DOI: 10.1007/s10479-022-04910-1
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    References listed on IDEAS

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    1. Seda Hezer & Yakup Kara, 2015. "A network-based shortest route model for parallel disassembly line balancing problem," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1849-1865, March.
    2. 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.
    3. Zixiang Li & Zeynel Abidin Çil & Süleyman Mete & Ibrahim Kucukkoc, 2020. "A fast branch, bound and remember algorithm for disassembly line balancing problem," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3220-3234, June.
    4. Urban, Timothy L. & Chiang, Wen-Chyuan, 2006. "An optimal piecewise-linear program for the U-line balancing problem with stochastic task times," European Journal of Operational Research, Elsevier, vol. 168(3), pages 771-782, February.
    5. Abdolreza Roshani & Davide Giglio, 2017. "Simulated annealing algorithms for the multi-manned assembly line balancing problem: minimising cycle time," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2731-2751, May.
    6. Mehmet Ali Ilgin & Hakan Akçay & Ceyhun Araz, 2017. "Disassembly line balancing using linear physical programming," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6108-6119, October.
    7. 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.
    8. Yaping Ren & Daoyuan Yu & Chaoyong Zhang & Guangdong Tian & Leilei Meng & Xiaoqiang Zhou, 2017. "An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem," International Journal of Production Research, Taylor & Francis Journals, vol. 55(24), pages 7302-7316, December.
    9. 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.
    10. Chiang, Wen-Chyuan & Urban, Timothy L., 2006. "The stochastic U-line balancing problem: A heuristic procedure," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1767-1781, December.
    11. Fred N. Silverman & John C. Carter, 1986. "A Cost-Based Methodology for Stochastic Line Balancing with Intermittent Line Stoppages," Management Science, INFORMS, vol. 32(4), pages 455-463, April.
    12. Yilin Fang & Hao Ming & Miqing Li & Quan Liu & Duc Truong Pham, 2020. "Multi-objective evolutionary simulated annealing optimisation for mixed-model multi-robotic disassembly line balancing with interval processing time," International Journal of Production Research, Taylor & Francis Journals, vol. 58(3), pages 846-862, February.
    13. Ming Liu & Xin Liu & Feng Chu & Feifeng Zheng & Chengbin Chu, 2020. "Robust disassembly line balancing with ambiguous task processing times," International Journal of Production Research, Taylor & Francis Journals, vol. 58(19), pages 5806-5835, October.
    14. 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.
    15. Eren Özceylan & Can B. Kalayci & Aşkıner Güngör & Surendra M. Gupta, 2019. "Disassembly line balancing problem: a review of the state of the art and future directions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4805-4827, August.
    16. Kalaycılar, Eda Göksoy & Azizoğlu, Meral & Yeralan, Sencer, 2016. "A disassembly line balancing problem with fixed number of workstations," European Journal of Operational Research, Elsevier, vol. 249(2), pages 592-604.
    17. Yu Zhang & Zeqiang Zhang & Chao Guan & Peiyu Xu, 2022. "Improved whale optimisation algorithm for two-sided disassembly line balancing problems considering part characteristic indexes," International Journal of Production Research, Taylor & Francis Journals, vol. 60(8), pages 2553-2571, April.
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