IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v34y2023i7d10.1007_s10845-022-01969-2.html
   My bibliography  Save this article

The integrated process planning and scheduling of flexible job-shop-type remanufacturing systems using improved artificial bee colony algorithm

Author

Listed:
  • Wenkang Zhang

    (University of Alberta)

  • Yufan Zheng

    (Xi’an Jiaotong-Liverpool University)

  • Rafiq Ahmad

    (University of Alberta)

Abstract

This study considers an integrated process planning and scheduling (IPPS) problem for remanufacturing systems incorporating parallel disassembly workstations, a flexible job-shop-type reprocessing shop, and parallel reassembly workstations. This IPPS problem aims to determine the allocation/sequence of end-of-life products on the disassembly/reassembly shops and make decisions on the process path selection, operation sequencing, workstation allocation, and selection for reprocessing jobs. To solve the problem, a mixed-integer programming model is first built to characterize it mathematically, and a novel extended network graph is designed to represent and solve this problem visually. Then, an improved artificial bee colony algorithm is proposed that can solve the IPPS problem of remanufacturing systems with disassembly, reworking and reassembly shops simultaneously. In this introduced algorithm, a 3-level real-number solution representation scheme is adopted for encoding and decoding processes, and efficient neighborhood search structures are designed to improve the quality and diversity of the population. Computational experiments were systematically conducted on serval test instances. The results show that the proposed algorithm is highly advantageous for solving the IPPS problems in the remanufacturing systems by comparing it with four baseline algorithms.

Suggested Citation

  • Wenkang Zhang & Yufan Zheng & Rafiq Ahmad, 2023. "The integrated process planning and scheduling of flexible job-shop-type remanufacturing systems using improved artificial bee colony algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2963-2988, October.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:7:d:10.1007_s10845-022-01969-2
    DOI: 10.1007/s10845-022-01969-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-022-01969-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-022-01969-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. R. Micale & C. M. La Fata & M. Enea & G. La Scalia, 2021. "Regenerative scheduling problem in engineer to order manufacturing: an economic assessment," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1913-1925, October.
    2. S. Zhang & T. N. Wong, 2018. "Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 585-601, March.
    3. Xiuli Wu & Junjian Peng & Xiao Xiao & Shaomin Wu, 2021. "An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 707-728, March.
    4. Guiliang Gong & Qianwang Deng & Raymond Chiong & Xuran Gong & Hezhiyuan Huang & Wenwu Han, 2020. "Remanufacturing-oriented process planning and scheduling: mathematical modelling and evolutionary optimisation," International Journal of Production Research, Taylor & Francis Journals, vol. 58(12), pages 3781-3799, June.
    5. Barzanji, Ramin & Naderi, Bahman & Begen, Mehmet A., 2020. "Decomposition algorithms for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 93(C).
    6. Zhigang Jiang & Ya Jiang & Yan Wang & Hua Zhang & Huajun Cao & Guangdong Tian, 2019. "A hybrid approach of rough set and case-based reasoning to remanufacturing process planning," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 19-32, January.
    7. Wenyuan Wang & Daniel Y. Mo & Yue Wang & Mitchell M. Tseng, 2019. "Assessing the cost structure of component reuse in a product family for remanufacturing," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 575-587, February.
    8. Daniel, V. & Guide, R. Jr., 1997. "Scheduling with priority dispatching rules and drum-buffer-rope in a recoverable manufacturing system," International Journal of Production Economics, Elsevier, vol. 53(1), pages 101-116, November.
    9. Min-Geun Kim & Jae-Min Yu & Dong-Ho Lee, 2015. "Scheduling algorithms for remanufacturing systems with parallel flow-shop-type reprocessing lines," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1819-1831, March.
    10. Pisut Pongchairerks & Voratas Kachitvichyanukul, 2009. "A two-level Particle Swarm Optimisation algorithm on Job-Shop Scheduling Problems," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 4(4), pages 390-411.
    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. Wenjie Wang & Guangdong Tian & Gang Yuan & Duc Truong Pham, 2023. "Energy-time tradeoffs for remanufacturing system scheduling using an invasive weed optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1065-1083, March.
    2. Qihao Liu & Xinyu Li & Liang Gao, 2021. "Mathematical modeling and a hybrid evolutionary algorithm for process planning," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 781-797, March.
    3. Zhu, Xuedong & Son, Junbo & Zhang, Xi & Wu, Jianguo, 2023. "Constraint programming and logic-based Benders decomposition for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 117(C).
    4. Abdessamad Ait El Cadi & Omar Souissi & Rabie Ben Atitallah & Nicolas Belanger & Abdelhakim Artiba, 2018. "Mathematical programming models for scheduling in a CPU/FPGA architecture with heterogeneous communication delays," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 629-640, March.
    5. Hassan Zohali & Bahman Naderi & Vahid Roshanaei, 2022. "Solving the Type-2 Assembly Line Balancing with Setups Using Logic-Based Benders Decomposition," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 315-332, January.
    6. Tomoko Sakiyama & Ikuo Arizono, 2018. "Coordination of Pheromone Deposition Might Solve Time-Constrained Travelling Salesman Problem," Complexity, Hindawi, vol. 2018, pages 1-5, December.
    7. Jiyoung Jung & Kundo Park & Byungjin Cho & Jinkyoo Park & Seunghwa Ryu, 2023. "Optimization of injection molding process using multi-objective bayesian optimization and constrained generative inverse design networks," Journal of Intelligent Manufacturing, Springer, vol. 34(8), pages 3623-3636, December.
    8. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    9. Fujimoto, Takahiro & Park, Young Won, 2014. "Balancing supply chain competitiveness and robustness through “virtual dual sourcing”: Lessons from the Great East Japan Earthquake," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 429-436.
    10. Yanbin Du & Guohua He & Bo Li & Zhijie Zhou & Guoao Wu, 2022. "In-service machine tool remanufacturing: a sustainable resource-saving and high-valued recovery approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1335-1358, January.
    11. Pisut Pongchairerks, 2019. "A Two-Level Metaheuristic Algorithm for the Job-Shop Scheduling Problem," Complexity, Hindawi, vol. 2019, pages 1-11, March.
    12. Mina Roohnavazfar & Seyed Hamid Reza Pasandideh, 2022. "Decomposition algorithm for the multi-trip single vehicle routing problem with AND-type precedence constraints," Operational Research, Springer, vol. 22(4), pages 4253-4285, September.
    13. Mehmet Ali Soytaş & Damla Durak Uşar & Meltem Denizel, 2022. "Estimation of the static corporate sustainability interactions," International Journal of Production Research, Taylor & Francis Journals, vol. 60(4), pages 1245-1264, February.
    14. Sicheng Zhang & T.N. Wong, 2016. "Studying the impact of sequence-dependent set-up times in integrated process planning and scheduling with E-ACO heuristic," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4815-4838, August.
    15. Pai Liu & Xi Zhang & Zhongshun Shi & Zewen Huang, 2017. "Simulation Optimization for MRO Systems Operations," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-23, April.
    16. Zhang, Sicheng & Li, Xiang & Zhang, Bowen & Wang, Shouyang, 2020. "Multi-objective optimisation in flexible assembly job shop scheduling using a distributed ant colony system," European Journal of Operational Research, Elsevier, vol. 283(2), pages 441-460.
    17. Yaping Ren & Xinyu Lu & Hongfei Guo & Zhaokang Xie & Haoyang Zhang & Chaoyong Zhang, 2023. "A Review of Combinatorial Optimization Problems in Reverse Logistics and Remanufacturing for End-of-Life Products," Mathematics, MDPI, vol. 11(2), pages 1-24, January.
    18. Mengrui Zhu & Yun Yang & Xiaobing Feng & Zhengchun Du & Jianguo Yang, 2023. "Robust modeling method for thermal error of CNC machine tools based on random forest algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 2013-2026, April.
    19. Chao Liu & Peifeng Niu & Guoqiang Li & Yunpeng Ma & Weiping Zhang & Ke Chen, 2018. "Enhanced shuffled frog-leaping algorithm for solving numerical function optimization problems," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1133-1153, June.
    20. Hyun Cheol Lee & Chunghun Ha, 2019. "Sustainable Integrated Process Planning and Scheduling Optimization Using a Genetic Algorithm with an Integrated Chromosome Representation," Sustainability, MDPI, vol. 11(2), pages 1-23, January.

    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:spr:joinma:v:34:y:2023:i:7:d:10.1007_s10845-022-01969-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.