LAPSE:2018.0276
Published Article
LAPSE:2018.0276
A General State-Space Formulation for Online Scheduling
July 31, 2018
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.
Record ID
Keywords
bio-manufacturing, mixed-integer linear programming, Model Predictive Control, state-space model, uncertainty
Subject
Suggested Citation
Gupta D, Maravelias CT. A General State-Space Formulation for Online Scheduling. (2018). LAPSE:2018.0276
Author Affiliations
Journal Name
Processes
Volume
5
Issue
4
Article Number
E69
Year
2017
Publication Date
2017-11-08
Published Version
ISSN
2227-9717
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Original Submission
Other Meta
PII: pr5040069, Publication Type: Journal Article
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LAPSE:2018.0276
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doi:10.3390/pr5040069
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[v1] (Original Submission)
Jul 31, 2018
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Jul 31, 2018
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