Submitted:
17 October 2017
Posted:
18 October 2017
You are already at the latest version
Abstract
We present a generalized state-space model formulation particularly motivated by an online scheduling perspective. 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.
Keywords:
state-space model
; uncertainty
; mixed-integer linear programming
; model predictive control
; bio-manufacturing
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