IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v141y2013i1p112-126.html
   My bibliography  Save this article

Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns

Author

Listed:
  • Xiong, Jian
  • Xing, Li-ning
  • Chen, Ying-wu

Abstract

This study addresses robust scheduling for a flexible job-shop scheduling problem with random machine breakdowns. Two objectives – makespan and robustness – are simultaneously considered. Robustness is indicated by the expected value of the relative difference between the deterministic and actual makespan. Utilizing the available information about machine breakdowns, two surrogate measures for robustness are developed. Specifically, the first suggested surrogate measure considers the probability of machine breakdowns, while the second surrogate measure considers the location of float times and machine breakdowns. To address this problem, a multi-objective evolutionary algorithm is presented in this paper. The experimental results indicate that, compared with several other existing surrogate measures, the first suggested surrogate measure performs better for small cases, while the second surrogate measure performs better for both small and relatively large cases.

Suggested Citation

  • Xiong, Jian & Xing, Li-ning & Chen, Ying-wu, 2013. "Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns," International Journal of Production Economics, Elsevier, vol. 141(1), pages 112-126.
    • Handle: RePEc:eee:proeco:v:141:y:2013:i:1:p:112-126
    DOI: 10.1016/j.ijpe.2012.04.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527312001739
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2012.04.015?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. Al-Fawzan, M. A. & Haouari, Mohamed, 2005. "A bi-objective model for robust resource-constrained project scheduling," International Journal of Production Economics, Elsevier, vol. 96(2), pages 175-187, May.
    2. Kacem, Imed & Hammadi, Slim & Borne, Pierre, 2002. "Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 60(3), pages 245-276.
    3. HazIr, Öncü & Haouari, Mohamed & Erel, Erdal, 2010. "Robust scheduling and robustness measures for the discrete time/cost trade-off problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 633-643, December.
    4. Al-Hinai, Nasr & ElMekkawy, T.Y., 2011. "Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm," International Journal of Production Economics, Elsevier, vol. 132(2), pages 279-291, August.
    5. Herroelen, Willy & Leus, Roel, 2005. "Project scheduling under uncertainty: Survey and research potentials," European Journal of Operational Research, Elsevier, vol. 165(2), pages 289-306, September.
    6. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    7. Shadrokh, Shahram & Kianfar, Fereydoon, 2007. "A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty," European Journal of Operational Research, Elsevier, vol. 181(1), pages 86-101, August.
    8. Van de Vonder, Stijn & Demeulemeester, Erik & Herroelen, Willy, 2008. "Proactive heuristic procedures for robust project scheduling: An experimental analysis," European Journal of Operational Research, Elsevier, vol. 189(3), pages 723-733, September.
    9. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    10. Richard L. Daniels & Panagiotis Kouvelis, 1995. "Robust Scheduling to Hedge Against Processing Time Uncertainty in Single-Stage Production," Management Science, INFORMS, vol. 41(2), pages 363-376, February.
    11. Lambrechts, Olivier & Demeulemeester, Erik & Herroelen, Willy, 2008. "A tabu search procedure for developing robust predictive project schedules," International Journal of Production Economics, Elsevier, vol. 111(2), pages 493-508, February.
    12. S. David Wu & Eui-Seok Byeon & Robert H. Storer, 1999. "A Graph-Theoretic Decomposition of the Job Shop Scheduling Problem to Achieve Scheduling Robustness," Operations Research, INFORMS, vol. 47(1), pages 113-124, February.
    13. Kobylanski, Przemyslaw & Kuchta, Dorota, 2007. "A note on the paper by M. A. Al-Fawzan and M. Haouari about a bi-objective problem for robust resource-constrained project scheduling," International Journal of Production Economics, Elsevier, vol. 107(2), pages 496-501, June.
    14. Xia, Yu & Chen, Bintong & Yue, Jinfeng, 2008. "Job sequencing and due date assignment in a single machine shop with uncertain processing times," European Journal of Operational Research, Elsevier, vol. 184(1), pages 63-75, January.
    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. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    2. Shichang Xiao & Shudong Sun & Jionghua (Judy) Jin, 2017. "Surrogate Measures for the Robust Scheduling of Stochastic Job Shop Scheduling Problems," Energies, MDPI, vol. 10(4), pages 1-26, April.
    3. Choo Jun Tan & Siew Chin Neoh & Chee Peng Lim & Samer Hanoun & Wai Peng Wong & Chu Kong Loo & Li Zhang & Saeid Nahavandi, 2019. "Application of an evolutionary algorithm-based ensemble model to job-shop scheduling," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 879-890, February.
    4. Pablo Valledor & Alberto Gomez & Javier Puente & Isabel Fernandez, 2022. "Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments with Multiple Objectives Using the Hybrid Dynamic Non-Dominated Sorting Genetic II Algorithm," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    5. Shichang Xiao & Zigao Wu & Hongyan Dui, 2022. "Resilience-Based Surrogate Robustness Measure and Optimization Method for Robust Job-Shop Scheduling," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    6. Ferreira, Cristiane & Figueira, Gonçalo & Amorim, Pedro, 2022. "Effective and interpretable dispatching rules for dynamic job shops via guided empirical learning," Omega, Elsevier, vol. 111(C).
    7. Taejong Joo & Hyunyoung Jun & Dongmin Shin, 2022. "Task Allocation in Human–Machine Manufacturing Systems Using Deep Reinforcement Learning," Sustainability, MDPI, vol. 14(4), pages 1-18, February.
    8. Alper Türkyılmaz & Özlem Şenvar & İrem Ünal & Serol Bulkan, 2020. "A research survey: heuristic approaches for solving multi objective flexible job shop problems," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1949-1983, December.
    9. Jain, S. & Foley, W.J., 2016. "Dispatching strategies for managing uncertainties in automated manufacturing systems," European Journal of Operational Research, Elsevier, vol. 248(1), pages 328-341.
    10. Yuri N. Sotskov & Natalja M. Matsveichuk & Vadzim D. Hatsura, 2020. "Schedule Execution for Two-Machine Job-Shop to Minimize Makespan with Uncertain Processing Times," Mathematics, MDPI, vol. 8(8), pages 1-51, August.
    11. Li, Xinyu & Gao, Liang, 2016. "An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem," International Journal of Production Economics, Elsevier, vol. 174(C), pages 93-110.
    12. Che, Ada & Feng, Jianguang & Chen, Haoxun & Chu, Chengbin, 2015. "Robust optimization for the cyclic hoist scheduling problem," European Journal of Operational Research, Elsevier, vol. 240(3), pages 627-636.
    13. Abdelhamid Boudjelida, 2019. "On the robustness of joint production and maintenance scheduling in presence of uncertainties," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1515-1530, April.
    14. Zigao Wu & Shaohua Yu & Tiancheng Li, 2019. "A Meta-Model-Based Multi-Objective Evolutionary Approach to Robust Job Shop Scheduling," Mathematics, MDPI, vol. 7(6), pages 1-19, June.
    15. Berti, Nicola & Finco, Serena & Battaïa, Olga & Delorme, Xavier, 2021. "Ageing workforce effects in Dual-Resource Constrained job-shop scheduling," International Journal of Production Economics, Elsevier, vol. 237(C).
    16. Alejandro Vital-Soto & Mohammed Fazle Baki & Ahmed Azab, 2023. "A multi-objective mathematical model and evolutionary algorithm for the dual-resource flexible job-shop scheduling problem with sequencing flexibility," Flexible Services and Manufacturing Journal, Springer, vol. 35(3), pages 626-668, September.

    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. Al-Hinai, Nasr & ElMekkawy, T.Y., 2011. "Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm," International Journal of Production Economics, Elsevier, vol. 132(2), pages 279-291, August.
    2. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    3. Shichang Xiao & Shudong Sun & Jionghua (Judy) Jin, 2017. "Surrogate Measures for the Robust Scheduling of Stochastic Job Shop Scheduling Problems," Energies, MDPI, vol. 10(4), pages 1-26, April.
    4. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    5. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Frank Werner, 2016. "Schedule robustness analysis with the help of attainable sets in continuous flow problem under capacity disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(11), pages 3397-3413, June.
    6. HazIr, Öncü & Erel, Erdal & Günalay, Yavuz, 2011. "Robust optimization models for the discrete time/cost trade-off problem," International Journal of Production Economics, Elsevier, vol. 130(1), pages 87-95, March.
    7. HazIr, Öncü & Haouari, Mohamed & Erel, Erdal, 2010. "Robust scheduling and robustness measures for the discrete time/cost trade-off problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 633-643, December.
    8. Said, Samer S. & Haouari, Mohamed, 2015. "A hybrid simulation-optimization approach for the robust Discrete Time/Cost Trade-off Problem," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 628-636.
    9. Shichang Xiao & Zigao Wu & Hongyan Dui, 2022. "Resilience-Based Surrogate Robustness Measure and Optimization Method for Robust Job-Shop Scheduling," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    10. Hartmann, Sönke & Briskorn, Dirk, 2010. "A survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 207(1), pages 1-14, November.
    11. Selcuk Goren & Ihsan Sabuncuoglu & Utku Koc, 2012. "Optimization of schedule stability and efficiency under processing time variability and random machine breakdowns in a job shop environment," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(1), pages 26-38, February.
    12. Hartmann, Sönke & Briskorn, Dirk, 2008. "A survey of variants and extensions of the resource-constrained project scheduling problem," Working Paper Series 02/2008, Hamburg School of Business Administration (HSBA).
    13. Briskorn, Dirk & Leung, Joseph & Pinedo, Michael, 2008. "Robust scheduling on a single machine usinge time buffers," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 639, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    14. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.
    15. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    16. Servranckx, Tom & Vanhoucke, Mario, 2019. "Strategies for project scheduling with alternative subgraphs under uncertainty: similar and dissimilar sets of schedules," European Journal of Operational Research, Elsevier, vol. 279(1), pages 38-53.
    17. Morteza Davari & Erik Demeulemeester, 2019. "The proactive and reactive resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 22(2), pages 211-237, April.
    18. Ripon K. Chakrabortty & Ruhul A. Sarker & Daryl L. Essam, 2020. "Single mode resource constrained project scheduling with unreliable resources," Operational Research, Springer, vol. 20(3), pages 1369-1403, September.
    19. Janusz Kulejewski & Nabi Ibadov & Jerzy Rosłon & Jacek Zawistowski, 2021. "Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling," Energies, MDPI, vol. 14(18), pages 1-15, September.
    20. Gang Xuan & Win-Chin Lin & Shuenn-Ren Cheng & Wei-Lun Shen & Po-An Pan & Chih-Ling Kuo & Chin-Chia Wu, 2022. "A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios," Mathematics, MDPI, vol. 10(13), pages 1-17, June.

    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:141:y:2013:i:1:p:112-126. 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.