IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v240y2015i2p338-354.html
   My bibliography  Save this article

Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time

Author

Listed:
  • Xiong, Fuli
  • Xing, Keyi
  • Wang, Feng

Abstract

This study considers a hybrid assembly-differentiation flowshop scheduling problem (HADFSP), in which there are three production stages, including components manufacturing, assembly, and differentiation. All the components of a job are processed on different machines at the first stage. Subsequently, they are assembled together on a common single machine at the second stage. At the third stage, each job of a particular type is processed on a dedicated machine. The objective is to find a job schedule to minimize total flow time (TFT). At first, a mixed integer programming (MIP) model is formulated and then some properties of the optimal solution are presented. Since the NP-hardness of the problem, two fast heuristics (SPT-based heuristic and NEH-based heuristic) and three hybrid meta-heuristics (HGA-VNS, HDDE-VNS and HEDA-VNS) are developed for solving medium- and large-size problems. In order to evaluate the performances of the proposed algorithms, a lower bound for the HADFSP with TFT criteria (HADFSP-TFT) is established. The MIP model and the proposed algorithms are compared on randomly generated problems. Computational results show the effectiveness of the MIP model and the proposed algorithms. The computational analysis indicates that, in average, the HDDE-VNS performs better and more robustly than the other two meta-heuristics, whereas the NEH heuristic consume little time and could reach reasonable solutions.

Suggested Citation

  • Xiong, Fuli & Xing, Keyi & Wang, Feng, 2015. "Scheduling a hybrid assembly-differentiation flowshop to minimize total flow time," European Journal of Operational Research, Elsevier, vol. 240(2), pages 338-354.
    • Handle: RePEc:eee:ejores:v:240:y:2015:i:2:p:338-354
    DOI: 10.1016/j.ejor.2014.07.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714005554
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2014.07.004?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. Brah, Shaukat A. & Loo, Luan Luan, 1999. "Heuristics for scheduling in a flow shop with multiple processors," European Journal of Operational Research, Elsevier, vol. 113(1), pages 113-122, February.
    2. Lejeune, M.A., 2006. "A variable neighborhood decomposition search method for supply chain management planning problems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 959-976, December.
    3. Framinan, Jose M. & Leisten, Rainer & Ruiz-Usano, Rafael, 2002. "Efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime minimisation," European Journal of Operational Research, Elsevier, vol. 141(3), pages 559-569, September.
    4. Chung-Yee Lee & T. C. E. Cheng & B. M. T. Lin, 1993. "Minimizing the Makespan in the 3-Machine Assembly-Type Flowshop Scheduling Problem," Management Science, INFORMS, vol. 39(5), pages 616-625, May.
    5. Ruiz, Ruben & Stutzle, Thomas, 2008. "An Iterated Greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1143-1159, June.
    6. Eglese, R. W., 1990. "Simulated annealing: A tool for operational research," European Journal of Operational Research, Elsevier, vol. 46(3), pages 271-281, June.
    7. C. N. Potts & S. V. Sevast'janov & V. A. Strusevich & L. N. Van Wassenhove & C. M. Zwaneveld, 1995. "The Two-Stage Assembly Scheduling Problem: Complexity and Approximation," Operations Research, INFORMS, vol. 43(2), pages 346-355, April.
    8. Allahverdi, Ali & Aydilek, Harun, 2014. "Total completion time with makespan constraint in no-wait flowshops with setup times," European Journal of Operational Research, Elsevier, vol. 238(3), pages 724-734.
    9. Wang, Sheng-yao & Wang, Ling & Liu, Min & Xu, Ye, 2013. "An effective estimation of distribution algorithm for solving the distributed permutation flow-shop scheduling problem," International Journal of Production Economics, Elsevier, vol. 145(1), pages 387-396.
    10. Figielska, Ewa, 2014. "A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages," European Journal of Operational Research, Elsevier, vol. 236(2), pages 433-444.
    11. Chen, Shih-Hsin & Chen, Min-Chih, 2013. "Addressing the advantages of using ensemble probabilistic models in Estimation of Distribution Algorithms for scheduling problems," International Journal of Production Economics, Elsevier, vol. 141(1), pages 24-33.
    12. De Giovanni, L. & Pezzella, F., 2010. "An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem," European Journal of Operational Research, Elsevier, vol. 200(2), pages 395-408, January.
    13. Tseng, Lin-Yu & Lin, Ya-Tai, 2009. "A hybrid genetic local search algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 198(1), pages 84-92, October.
    14. Ruiz, Rubén & Maroto, Concepciøn & Alcaraz, Javier, 2006. "Two new robust genetic algorithms for the flowshop scheduling problem," Omega, Elsevier, vol. 34(5), pages 461-476, October.
    15. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    16. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
    17. Ruiz, Ruben & Stutzle, Thomas, 2007. "A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2033-2049, March.
    18. Al-Anzi, Fawaz S. & Allahverdi, Ali, 2007. "A self-adaptive differential evolution heuristic for two-stage assembly scheduling problem to minimize maximum lateness with setup times," European Journal of Operational Research, Elsevier, vol. 182(1), pages 80-94, October.
    19. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    20. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
    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. 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.
    2. Wang, Kai & Qin, Hu & Huang, Yun & Luo, Mengwen & Zhou, Lei, 2021. "Surgery scheduling in outpatient procedure centre with re-entrant patient flow and fuzzy service times," Omega, Elsevier, vol. 102(C).
    3. Wu, Xueqi & Che, Ada, 2020. "Energy-efficient no-wait permutation flow shop scheduling by adaptive multi-objective variable neighborhood search," Omega, Elsevier, vol. 94(C).
    4. Framinan, Jose M. & Perez-Gonzalez, Paz & Fernandez-Viagas, Victor, 2019. "Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures," European Journal of Operational Research, Elsevier, vol. 273(2), pages 401-417.

    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. Hatami, Sara & Ruiz, Rubén & Andrés-Romano, Carlos, 2015. "Heuristics and metaheuristics for the distributed assembly permutation flowshop scheduling problem with sequence dependent setup times," International Journal of Production Economics, Elsevier, vol. 169(C), pages 76-88.
    2. Pan, Quan-Ke & Ruiz, Rubén, 2012. "Local search methods for the flowshop scheduling problem with flowtime minimization," European Journal of Operational Research, Elsevier, vol. 222(1), pages 31-43.
    3. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
    4. Pan, Quan-Ke & Gao, Liang & Li, Xin-Yu & Gao, Kai-Zhou, 2017. "Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times," Applied Mathematics and Computation, Elsevier, vol. 303(C), pages 89-112.
    5. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    6. Pessoa, Luciana S. & Andrade, Carlos E., 2018. "Heuristics for a flowshop scheduling problem with stepwise job objective function," European Journal of Operational Research, Elsevier, vol. 266(3), pages 950-962.
    7. Pagnozzi, Federico & Stützle, Thomas, 2019. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems," European Journal of Operational Research, Elsevier, vol. 276(2), pages 409-421.
    8. Arshad Ali & Yuvraj Gajpal & Tarek Y. Elmekkawy, 2021. "Distributed permutation flowshop scheduling problem with total completion time objective," OPSEARCH, Springer;Operational Research Society of India, vol. 58(2), pages 425-447, June.
    9. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
    10. Ciavotta, Michele & Minella, Gerardo & Ruiz, Rubén, 2013. "Multi-objective sequence dependent setup times permutation flowshop: A new algorithm and a comprehensive study," European Journal of Operational Research, Elsevier, vol. 227(2), pages 301-313.
    11. Fernandez-Viagas, Victor & Talens, Carla & Framinan, Jose M., 2022. "Assembly flowshop scheduling problem: Speed-up procedure and computational evaluation," European Journal of Operational Research, Elsevier, vol. 299(3), pages 869-882.
    12. Wang, Chuyang & Li, Xiaoping & Wang, Qian, 2010. "Accelerated tabu search for no-wait flowshop scheduling problem with maximum lateness criterion," European Journal of Operational Research, Elsevier, vol. 206(1), pages 64-72, October.
    13. Vallada, Eva & Ruiz, Rubén & Framinan, Jose M., 2015. "New hard benchmark for flowshop scheduling problems minimising makespan," European Journal of Operational Research, Elsevier, vol. 240(3), pages 666-677.
    14. Naderi, Bahman & Ruiz, Rubén, 2014. "A scatter search algorithm for the distributed permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 239(2), pages 323-334.
    15. Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.
    16. Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
    17. Niloy J. Mukherjee & Subhash C. Sarin & Daniel A. Neira, 2023. "Lot streaming for a two-stage assembly system in the presence of handling costs," Journal of Scheduling, Springer, vol. 26(4), pages 335-351, August.
    18. Guiliang Gong & Raymond Chiong & Qianwang Deng & Qiang Luo, 2020. "A memetic algorithm for multi-objective distributed production scheduling: minimizing the makespan and total energy consumption," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1443-1466, August.
    19. Chen, Shih-Hsin & Chen, Min-Chih, 2013. "Addressing the advantages of using ensemble probabilistic models in Estimation of Distribution Algorithms for scheduling problems," International Journal of Production Economics, Elsevier, vol. 141(1), pages 24-33.
    20. Sioud, A. & Gagné, C., 2018. "Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 264(1), pages 66-73.

    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:eee:ejores:v:240:y:2015:i:2:p:338-354. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.