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The Classification Of Scheduling Problems Under Production Uncertainty

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
One of the most important issue regarding scheduling problem is production uncertainty. From the standpoint of real-world scheduling problem, it is necessary to find solution of building the schedule which can be insensitive to production disruptions such as machine breakdowns, incorrectly estimated time interval of machines maintenance, absence of workers, unavailability of materials or tooling, production defects, variable processing times, etc. This research study is conducted to answer the question: how the researchers cope with the problem of production uncertainty taking into account the scheduling problem? Our investigation focuses on approaches developed for scheduling with production uncertainty consideration. Among these approaches the most popular ones are: reactive scheduling, proactive scheduling, predictive scheduling and robust predictive-reactive approaches. A brief explanation of individual approaches are presented. Further, models of uncertainty used in scheduling approaches are highlighted.
Rocznik
Strony
245--256
Opis fizyczny
Bibliogr. 30 poz.
Twórcy
  • Cracow University of Technology, Institute of Production Engineering and Automation, al. Jana Pawla II 37, 31-864 Cracow, Poland
  • Cracow University of Technology, Institute of Production Engineering and Automation, al. Jana Pawla II 37, 31-864 Cracow, Poland
Bibliografia
  • Al-Hinai N. & 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, Vol.132, No.2, pp. 279-291.
  • Aytug H., Lawley M.A., McKay K., Mohan S. & Uzsoy R., (2005), "Executing production schedules in the face of uncertainties: A review and some future directions", European Journal and Operational Research, Vol.161, No.1, pp. 86-110.
  • Bidot J., (2005), "A general framework integrating techniques for scheduling under uncertainty", PhD dissertation, Institut National Polytechnique de Toulouse, France.
  • Billaut J.C., Maukrim A. & Sanlaville E., (2008), "Introduction to flexibility and robustness in scheduling", J.C. Billaut, A. Maukrim, E. Sanlaville (Ed.), Flexibility and robustness in scheduling, ISTE Ltd, London, pp. 15-31.
  • Ghezail F. Pierreval H. & Hajri-Gabouj S., (2010) "Analysis of robustness in proactive scheduling: A graphical approach", Computers & Industrial Engineering, Vol.58, No.2, pp. 193-195.
  • Gören S., (2002), "Robustness and stability measures for scheduling policies in a single machine enviroment", MSc dissertation, Bilkent University, Ankara.
  • Gören S. & Sabuncuoglu I., (2008) "Robustness and stability measures for scheduling: single-machine enviroment", IIE Transactions, 193–198, Vol.40, No.1, pp. 66-83.
  • Herroelen W. & Leus R., (2005), “Project scheduling under uncertainty: Survey and research potentials”, European Journal and Operational Research, Vol.165, No.2, pp. 289-306.
  • Klimek M., (2010), "Predictive-reactive scheduling with resource constraints", PhD dissertation, AGH University of Technology, Kraków.
  • Lei D., (2009) "Mutiple-objective production scheduling: a survey", International Journal of Advanced Manufacturing Technology, Vol.43, No.9-10, pp. 926-938.
  • Leon D.J., (1994), "Robustness measures and robust scheduling for jon shops", IIE Transactions, Vol.26, No.5, pp. 32-43.
  • Li Z., Ierapetritou M., (2008), "Process scheduling under uncertainty: Review and challenges", Computers & Chemical Engineering, Vol.32, No.4–5, pp.715–727.
  • Lin L., Gen M., Liang Y., Ohno K., (2012), "A hybrid EA for reactive flexible job-shop scheduling", Procedia Computer Science, Vol.12, pp.110-115.
  • Lin X., Janak S.L. & Floudas C.A., (2004), "A new robust optimization approach for scheduling under uncertainty:: I. Bounded uncertainty", Computers & Chemical Engineering, Vol.28, No.6–7, pp.1069–1085.
  • Murakami K.. & Morita H., (2009), "A method for generating robust schedule uncertainty in processing time", Biomedical Soft Computing and Human Sciences, Vol.15, No.1, pp. 47-52.
  • Nagar A., Haddock J. & Heragu S., (1995), "Mutiple and bicriteria scheduling: a literature survey processing time", European Journal and Operational Research, Vol.81, No.1, pp. 88-104.
  • Olteanu A., Pop F., Dobre C. & Cristea V., (2012), "A dynamic rescheduling algorithm for resource management in large scale dependable distributed systems", Computers & Mathematics with Applications, Vol.63, No.9, pp.1409–1423.
  • Ouelhadj D. & Pertovic S., (2009), "A surey of dynamic in manufacturing systems", Journal of Scheduling, Vol.12, No.4, pp. 417-431.
  • Palombarini J. & Martínez E., (2012), "SmartGantt – An intelligent system for real time rescheduling based on relational reinforcement learning", Expert Systems with Applications, Vol.39, No.11, pp.10251–10268.
  • Petrovic D. & Duenas A., (2006), "A fuzzy logic based production scheduling/rescheduling in the presence of uncertain disruptions", Fuzzy Sets and Systems, Vol.157, No.16, pp. 2273–2285.
  • Raheja A.S., Reddy K.R.B., Subramaniam V., (2003), "A generic mechanism for repairing job shop schedules", available at: http://dspace.mit.edu/bitstream/handle/1721.1/3744/-IMST010_Reddy.pdf?sequence=2 (accessed 12 July 2013).
  • Rasconi R., Cesta A. & Policella N., (2010), "Validating scheduling approaches against executional uncertainty", Journal of Intelligent Manufacturing, Vol.21, pp.49-64.
  • Sabuncuoglu I. & Bayiz M., (2003), "Analysis of reactive scheduling problems in a job shop environment", European Journal of Operational Research, Vol.126, No.3 pp. 567-586.
  • Sabuncuoglu I. & Gören S., (2009), "Hedging production schedules against uncertainty in manufacturing enviroment with a review of robustness and stability research", International Journal of Computer Integrated Manufacturing, Vol.22, No.6 pp. 138-157.
  • Sotskov Y.N. & Lai T.C., Werner F., (2013), "Measures of problem uncertainty for scheduling with interval processing times", OR Spectrum, Vol.35, pp.659-689.
  • Subramaniam V., Raheja A.S., (2003), "mAOR: A heuristic-based reactive repair mechanism for job-shop schedules", International Journal of Advanced Manu-facturing Technology, Vol.22, pp.669-680.
  • Vieira G.E., Herrmann J.W. & Lin A.E., (2003), "Rescheduling manufacturing systems: a framework of strategies, policies, and method", Journal of Scheduling, Vol.6, No.1, pp. 39-62.
  • Xiong J., Li-Ning X. & Ying-wu Cz., (2013), "Robust scheduling for multi-objecitve flexible job-shop problems with random machine breakdowns", International Journal of Production Economics, Vol.141, No.1, pp.112–126.
  • Yin J., Li T., Chen B. & Wang B., (2011), "Dynamic rescheduling expert system for hybrid flow shop with random disturbance", Procedia Engineering, Vol.15, pp. 3921–3925.
  • Zhao C. & Tang H., (2010), "Rescheduling problems with deteriorating jobs under disruptions", Applied Mathematical Modelling, Vol. 34, No.1, pp. 238–243.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b20f6c33-e48c-4333-a655-df75b383ea00
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