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.
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Sand, G., Engell, S., Märkert, A., Schultz, R. (2005). Applied Stochastic Integer Programming: Scheduling in the Processing Industries. In: Bock, H.G., Phu, H.X., Kostina, E., Rannacher, R. (eds) Modeling, Simulation and Optimization of Complex Processes. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27170-8_33
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DOI: https://doi.org/10.1007/3-540-27170-8_33
Publisher Name: Springer, Berlin, Heidelberg
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