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Processes 2017, 5(4), 69;

A General State-Space Formulation for Online Scheduling

Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA
Author to whom correspondence should be addressed.
Received: 2 October 2017 / Revised: 29 October 2017 / Accepted: 2 November 2017 / Published: 8 November 2017
(This article belongs to the Special Issue Combined Scheduling and Control)
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We present a generalized state-space model formulation particularly motivated by an online scheduling perspective, which allows modeling (1) task-delays and unit breakdowns; (2) fractional delays and unit downtimes, when using discrete-time grid; (3) variable batch-sizes; (4) robust scheduling through the use of conservative yield estimates and processing times; (5) feedback on task-yield estimates before the task finishes; (6) task termination during its execution; (7) post-production storage of material in unit; and (8) unit capacity degradation and maintenance. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings. Finally, we demonstrate the effectiveness of this model on a case study from the field of bio-manufacturing. View Full-Text
Keywords: state-space model; uncertainty; mixed-integer linear programming; model predictive control; bio-manufacturing state-space model; uncertainty; mixed-integer linear programming; model predictive control; bio-manufacturing

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Gupta, D.; Maravelias, C.T. A General State-Space Formulation for Online Scheduling. Processes 2017, 5, 69.

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