IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v179y2016icp239-258.html
   My bibliography  Save this article

Hybrid flow shop batching and scheduling with a bi-criteria objective

Author

Listed:
  • Shahvari, Omid
  • Logendran, Rasaratnam

Abstract

This paper addresses the hybrid flow shop batching and scheduling problem where sequence-dependent family setup times are present and the objective is to simultaneously minimize the weighted sum of the total weighted completion time and total weighted tardiness. In particular, it disregards the group technology assumptions by allowing for the possibility of splitting pre-determined groups of jobs into inconsistent batches in order to improve the operational efficiency. A benchmark of small size problems is considered to show the benefits of batching on group scheduling. Since the problem is strongly NP-hard, several algorithms based upon tabu search are developed at three levels, which move back and forth between batching and scheduling phases. Two algorithms incorporate tabu search into the framework of path-relinking to exploit the information on good solutions. These tabu search/path-relinking algorithms comprise several distinguishing features including two relinking procedures to effectively construct paths and the stage-based improvement procedure to consider the move interdependency. The best tabu search algorithm as a local search algorithm is compared to a population-based algorithm, and the superiority of the former over the latter is shown using a statistical experiment. The initial solution finding mechanism is implemented to trigger the search into the solution space. The efficiency and effectiveness of the best algorithm is verified with the help of the results found by CPLEX. The results show that the best algorithm, based on tabu search/path relinking and the stage-based improvement procedure, could find solutions at least as good as CPLEX, but in drastically shorter computational time. In order to reflect the real industry requirements, dynamic machine availability times, dynamic job release times, machine eligibility and machine capability for processing jobs, desired lower bounds on batch sizes, and job skipping are considered.

Suggested Citation

  • Shahvari, Omid & Logendran, Rasaratnam, 2016. "Hybrid flow shop batching and scheduling with a bi-criteria objective," International Journal of Production Economics, Elsevier, vol. 179(C), pages 239-258.
  • Handle: RePEc:eee:proeco:v:179:y:2016:i:c:p:239-258
    DOI: 10.1016/j.ijpe.2016.06.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527316301104
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2016.06.005?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. Allahverdi, Ali, 2015. "The third comprehensive survey on scheduling problems with setup times/costs," European Journal of Operational Research, Elsevier, vol. 246(2), pages 345-378.
    2. Taha Keshavarz & Nasser Salmasi, 2014. "Efficient upper and lower bounding methods for flowshop sequence-dependent group scheduling problems," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 8(3), pages 366-387.
    3. Bozorgirad, Mir Abbas & Logendran, Rasaratnam, 2013. "Bi-criteria group scheduling in hybrid flowshops," International Journal of Production Economics, Elsevier, vol. 145(2), pages 599-612.
    4. Dugardin, Frédéric & Yalaoui, Farouk & Amodeo, Lionel, 2010. "New multi-objective method to solve reentrant hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 203(1), pages 22-31, May.
    5. Rana, S. P. & Singh, N., 1994. "Group scheduling jobs on a single machine: A multi-objective approach with preemptive priority structure," European Journal of Operational Research, Elsevier, vol. 79(1), pages 38-50, November.
    6. Allahverdi, Ali & Ng, C.T. & Cheng, T.C.E. & Kovalyov, Mikhail Y., 2008. "A survey of scheduling problems with setup times or costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 985-1032, June.
    7. Taillard, E., 1993. "Benchmarks for basic scheduling problems," European Journal of Operational Research, Elsevier, vol. 64(2), pages 278-285, January.
    8. Yang, Wen-Hua & Chand, Suresh, 2008. "Learning and forgetting effects on a group scheduling problem," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1033-1044, June.
    9. Gupta, Jatinder N. D. & Darrow, William P., 1986. "The two-machine sequence dependent flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 24(3), pages 439-446, March.
    10. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 1996. "A fast tabu search algorithm for the permutation flow-shop problem," European Journal of Operational Research, Elsevier, vol. 91(1), pages 160-175, May.
    11. Schaller, Jeffrey E. & Gupta, Jatinder N. D. & Vakharia, Asoo J., 2000. "Scheduling a flowline manufacturing cell with sequence dependent family setup times," European Journal of Operational Research, Elsevier, vol. 125(2), pages 324-339, September.
    12. Scott Webster & Kenneth R. Baker, 1995. "Scheduling Groups of Jobs on a Single Machine," Operations Research, INFORMS, vol. 43(4), pages 692-703, August.
    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. Gang Du & Xi Liang & Chuanwang Sun, 2017. "Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows," Sustainability, MDPI, vol. 9(2), pages 1-22, February.
    2. Liu, Ming & Yang, Xuenan & Chu, Feng & Zhang, Jiantong & Chu, Chengbin, 2020. "Energy-oriented bi-objective optimization for the tempered glass scheduling," Omega, Elsevier, vol. 90(C).
    3. Omid Shahvari & Rasaratnam Logendran & Madjid Tavana, 2022. "An efficient model-based branch-and-price algorithm for unrelated-parallel machine batching and scheduling problems," Journal of Scheduling, Springer, vol. 25(5), pages 589-621, October.
    4. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    5. Mostafa Zandieh & Seyed Omid Mohaddesi, 2018. "Portfolio Rebalancing under Uncertainty Using Meta-heuristic Algorithm," Papers 1812.07635, arXiv.org.
    6. Ehsan Najafnejhad & Mahdieh Tavassoli Roodsari & Somayeh Sepahrom & Mojtaba Jenabzadeh, 2021. "A mathematical inventory model for a single-vendor multi-retailer supply chain based on the Vendor Management Inventory Policy," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 579-586, June.
    7. Majumder, Pinki & Mondal, Sankar Prasad & Bera, Uttam Kumar & Maiti, Manoranjan, 2016. "Application of Generalized Hukuhara derivative approach in an economic production quantity model with partial trade credit policy under fuzzy environment," Operations Research Perspectives, Elsevier, vol. 3(C), pages 77-91.
    8. Matin, Hossein N.Z. & Salmasi, Nasser & Shahvari, Omid, 2017. "Makespan minimization in flowshop batch processing problem with different batch compositions on machines," International Journal of Production Economics, Elsevier, vol. 193(C), pages 832-844.
    9. Ming Liu & Xuenan Yang & Jiantong Zhang & Chengbin Chu, 2017. "Scheduling a tempered glass manufacturing system: a three-stage hybrid flow shop model," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6084-6107, October.

    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. Bozorgirad, Mir Abbas & Logendran, Rasaratnam, 2013. "Bi-criteria group scheduling in hybrid flowshops," International Journal of Production Economics, Elsevier, vol. 145(2), pages 599-612.
    2. 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.
    3. Allahverdi, Ali, 2015. "The third comprehensive survey on scheduling problems with setup times/costs," European Journal of Operational Research, Elsevier, vol. 246(2), pages 345-378.
    4. Shen, Liji & Buscher, Udo, 2012. "Solving the serial batching problem in job shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 14-26.
    5. Hinder, Oliver & Mason, Andrew J., 2017. "A novel integer programing formulation for scheduling with family setup times on a single machine to minimize maximum lateness," European Journal of Operational Research, Elsevier, vol. 262(2), pages 411-423.
    6. Mohammad Reza Hosseinzadeh & Mehdi Heydari & Mohammad Mahdavi Mazdeh, 2022. "Mathematical modeling and two metaheuristic algorithms for integrated process planning and group scheduling with sequence-dependent setup time," Operational Research, Springer, vol. 22(5), pages 5055-5105, November.
    7. Agarwal, Anurag & Colak, Selcuk & Eryarsoy, Enes, 2006. "Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach," European Journal of Operational Research, Elsevier, vol. 169(3), pages 801-815, March.
    8. He, Xuan & Pan, Quan-Ke & Gao, Liang & Neufeld, Janis S., 2023. "An asymmetric traveling salesman problem based matheuristic algorithm for flowshop group scheduling problem," European Journal of Operational Research, Elsevier, vol. 310(2), pages 597-610.
    9. V. Anjana & R. Sridharan & P. N. Ram Kumar, 2020. "Metaheuristics for solving a multi-objective flow shop scheduling problem with sequence-dependent setup times," Journal of Scheduling, Springer, vol. 23(1), pages 49-69, February.
    10. Bagchi, Tapan P. & Gupta, Jatinder N.D. & Sriskandarajah, Chelliah, 2006. "A review of TSP based approaches for flowshop scheduling," European Journal of Operational Research, Elsevier, vol. 169(3), pages 816-854, March.
    11. Logendran, Rasaratnam & deSzoeke, Paula & Barnard, Faith, 2006. "Sequence-dependent group scheduling problems in flexible flow shops," International Journal of Production Economics, Elsevier, vol. 102(1), pages 66-86, July.
    12. Rossit, Daniel Alejandro & Tohmé, Fernando & Frutos, Mariano, 2018. "The Non-Permutation Flow-Shop scheduling problem: A literature review," Omega, Elsevier, vol. 77(C), pages 143-153.
    13. Geng, Zhichao & Yuan, Jinjiang & Yuan, Junling, 2018. "Scheduling with or without precedence relations on a serial-batch machine to minimize makespan and maximum cost," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 1-18.
    14. Jianxin Fang & Brenda Cheang & Andrew Lim, 2023. "Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey," Sustainability, MDPI, vol. 15(17), pages 1-44, August.
    15. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R & M. Calle, 2020. "Scheduling a dual-resource flexible job shop with makespan and due date-related criteria," Annals of Operations Research, Springer, vol. 291(1), pages 5-35, August.
    16. 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.
    17. Ghorbanzadeh, Masoumeh & Ranjbar, Mohammad, 2023. "Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints," European Journal of Operational Research, Elsevier, vol. 307(2), pages 519-537.
    18. Jean-Paul Watson & Laura Barbulescu & L. Darrell Whitley & Adele E. Howe, 2002. "Contrasting Structured and Random Permutation Flow-Shop Scheduling Problems: Search-Space Topology and Algorithm Performance," INFORMS Journal on Computing, INFORMS, vol. 14(2), pages 98-123, May.
    19. Kalczynski, Pawel Jan & Kamburowski, Jerzy, 2007. "On the NEH heuristic for minimizing the makespan in permutation flow shops," Omega, Elsevier, vol. 35(1), pages 53-60, February.
    20. Waldherr, Stefan & Knust, Sigrid, 2017. "Decomposition algorithms for synchronous flow shop problems with additional resources and setup times," European Journal of Operational Research, Elsevier, vol. 259(3), pages 847-863.

    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:proeco:v:179:y:2016:i:c:p:239-258. 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/ijpe .

    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.