Applied Stochastic Integer Programming: Scheduling in the Processing Industries

Guido Sand (), Sebastian Engell (), A. Märkert () and Rüdiger Schultz ()
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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

A chapter in Modeling, Simulation and Optimization of Complex Processes, 2005, pp 441-450 from Springer

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.

Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-27170-3_33

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DOI: 10.1007/3-540-27170-8_33

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