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Fuzzy Logic-Based Production Scheduling and Rescheduling in the Presence of Uncertainty

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Planning Production and Inventories in the Extended Enterprise

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 152))

Abstract

Production scheduling represents a major administrative and management issue in modern production planning and control. Ever since the first results of modern scheduling theory appeared some 50 years ago, scheduling research has attracted a lot of attention from both academia and industry. The diversity of scheduling problems, the large-scale dimension and dynamic nature of many modern problem-solving environments make this a very complex and difficult research area.

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Acknowledgements

The authors thank the Engineering and Physics Science Research Council (EPSRC), UK, for supporting this research (Grant No. GR/R95319/01 and GR/R95326/01). The authors also acknowledge the support of our industrial collaborators Sherwood Press Ltd., Nottingham, and Denby Pottery Company Ltd., UK.

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Authors and Affiliations

  1. Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science and IT, University of Nottingham, Nottingham, UK

    Sanja Petrovic

Authors
  1. Sanja Petrovic
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  2. Dobrila Petrovic
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  3. Edmund Burke
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Corresponding author

Correspondence to Sanja Petrovic .

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Editors and Affiliations

  1. , Decision Technologies C3-111, Intel Corporation, W. Chandler Blvd. 5000, Chandler, 85226, USA

    Karl G Kempf

  2. School of Industrial &, Systems Engineering, Georgia Institute of Technology, Ferst Drive NW., 765, Atlanta, 30332-0205, Georgia, USA

    Pınar Keskinocak

  3. , Edward P. Fitts Department of Industrial, North Carolina State University, Daniels Hall, Campus Box 7906 300, Raleigh, 27695, USA

    Reha Uzsoy

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Petrovic, S., Petrovic, D., Burke, E. (2011). Fuzzy Logic-Based Production Scheduling and Rescheduling in the Presence of Uncertainty. In: Kempf, K., Keskinocak, P., Uzsoy, R. (eds) Planning Production and Inventories in the Extended Enterprise. International Series in Operations Research & Management Science, vol 152. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8191-2_20

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