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Schedule robustness analysis with the help of attainable sets in continuous flow problem under capacity disruptions

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  • Dmitry Ivanov
  • Alexandre Dolgui
  • Boris Sokolov
  • Frank Werner

Abstract

Continuous flow scheduling problems have their place in many industries such as gas, oil, chemicals, glass and fluids production as well as production of granular goods and steel details. The disruptions in processing capacities may result in schedule performance decrease. In this paper, we develop a new method for robustness analysis of those schedules that are formulated in continuous time in the state-space domain. The developed method is based on attainable sets (ASs) that allow computing a form to represent the states and performance of schedules in regard to different capacity degradation levels. Having such a form, it becomes possible to estimate the schedule robustness. The technical development and approximation of ASs are presented. A robustness index is developed on the basis of the minimax regret approach, and it can be used for decision-makers regarding the trade-off ‘performance vs. robustness’. As such, it becomes possible to compare maximal possible profits in situations without disruptions and realistic profits subject to some robustness investments and costs of protection against disruptions. With the presented results, it becomes possible to obtain ASs for interval data with no a priori information about perturbation impacts, i.e. for non-stationary perturbations. ASs permit to consider perturbations and schedule performances as time functions . Perturbation functions may be set up for different uncertainty scenarios, including interval perturbations.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:11:p:3397-3413
    DOI: 10.1080/00207543.2015.1129467
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    References listed on IDEAS

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    1. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    2. 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.
    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. Forst, Frank G., 1995. "Bicriterion stochastic scheduling on one or more machines," European Journal of Operational Research, Elsevier, vol. 80(2), pages 404-409, January.
    5. Chauhan, Satyaveer S. & Dolgui, Alexandre & Proth, Jean-Marie, 2009. "A continuous model for supply planning of assembly systems with stochastic component procurement times," International Journal of Production Economics, Elsevier, vol. 120(2), pages 411-417, August.
    6. Xiaoqiang Cai & Xianyi Wu & Xian Zhou, 2009. "Stochastic Scheduling Subject to Preemptive-Repeat Breakdowns with Incomplete Information," Operations Research, INFORMS, vol. 57(5), pages 1236-1249, October.
    7. Artigues, Christian & Billaut, Jean-Charles & Esswein, Carl, 2005. "Maximization of solution flexibility for robust shop scheduling," European Journal of Operational Research, Elsevier, vol. 165(2), pages 314-328, September.
    8. 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.
    9. 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.
    10. Sotskov, Yuri N. & Dolgui, Alexandre & Portmann, Marie-Claude, 2006. "Stability analysis of an optimal balance for an assembly line with fixed cycle time," European Journal of Operational Research, Elsevier, vol. 168(3), pages 783-797, February.
    11. Roy, Bernard, 2010. "Robustness in operational research and decision aiding: A multi-faceted issue," European Journal of Operational Research, Elsevier, vol. 200(3), pages 629-638, 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.
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    Cited by:

    1. Li, Guo & Li, Na & Sambandam, Narayanasamy & Sethi, Suresh P. & Zhang, Faping, 2018. "Flow shop scheduling with jobs arriving at different times," International Journal of Production Economics, Elsevier, vol. 206(C), pages 250-260.
    2. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    3. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.

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