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Applied Stochastic Integer Programming: Scheduling in the Processing Industries

In: Modeling, Simulation and Optimization of Complex Processes

Author

Listed:
  • Guido Sand

    (Universität Dortmund, Department of Biochemical and Chemical Engineering)

  • Sebastian Engell

    (Universität Dortmund, Department of Biochemical and Chemical Engineering)

  • A. Märkert

    (Universität Duisburg-Essen, Institute of Mathematics)

  • Rüdiger Schultz

    (Universität Duisburg-Essen, Institute of Mathematics)

Abstract

Summary In this contribution, we consider scheduling problems of flexible batch plants in the processing industries. Special emphasis is put on the aspect of uncertainty, which is undoubtedly relevant but was often neglected so far. Motivated by a real-world example process, we describe an “engineered” solution concept based upon two-stage stochastic integer programming along with a decomposition-based solution algorithm and numerical experiences.

Suggested Citation

  • Guido Sand & Sebastian Engell & A. Märkert & Rüdiger Schultz, 2005. "Applied Stochastic Integer Programming: Scheduling in the Processing Industries," Springer Books, in: Hans Georg Bock & Hoang Xuan Phu & Ekaterina Kostina & Rolf Rannacher (ed.), Modeling, Simulation and Optimization of Complex Processes, pages 441-450, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27170-3_33
    DOI: 10.1007/3-540-27170-8_33
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