TY - JOUR
T1 - On deterministic online scheduling
T2 - Major considerations, paradoxes and remedies
AU - Gupta, Dhruv
AU - Maravelias, Christos T.
N1 - Funding Information:
The authors would like to acknowledge support from the National Science Foundation under grants CMMI-1334933 and CBET-1264096 , as well as the Petroleum Research Fund under grant 53313-ND9 . CTM would like to thank Dr. James Rawlings for fruitful discussions on model predictive control and, specifically, on the role of feedback.
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2016/11/2
Y1 - 2016/11/2
N2 - Despite research in the area, the relationship between the (open-loop) optimization problem and the quality of the (closed-loop) implemented schedule is poorly understood. Accordingly, we first show that open-loop and closed-loop scheduling are two different problems, even in the deterministic case. Thereafter, we investigate attributes of the open-loop problem and the rescheduling algorithm that affect closed-loop schedule quality. We find that it is important to reschedule periodically even when there are no “trigger” events. We show that solving the open-loop problem suboptimally does not lead to poor closed-loop solutions; instead, suboptimal solutions are corrected through feedback. We also observe that there exist thresholds for rescheduling frequency and moving horizon length, operating outside of which leads to substantial performance deterioration. Fourth, we show that the design attributes work in conjunction, hence, studying them simultaneously is important. Finally, we explore objective function modifications and constraint addition as methods to improve performance.
AB - Despite research in the area, the relationship between the (open-loop) optimization problem and the quality of the (closed-loop) implemented schedule is poorly understood. Accordingly, we first show that open-loop and closed-loop scheduling are two different problems, even in the deterministic case. Thereafter, we investigate attributes of the open-loop problem and the rescheduling algorithm that affect closed-loop schedule quality. We find that it is important to reschedule periodically even when there are no “trigger” events. We show that solving the open-loop problem suboptimally does not lead to poor closed-loop solutions; instead, suboptimal solutions are corrected through feedback. We also observe that there exist thresholds for rescheduling frequency and moving horizon length, operating outside of which leads to substantial performance deterioration. Fourth, we show that the design attributes work in conjunction, hence, studying them simultaneously is important. Finally, we explore objective function modifications and constraint addition as methods to improve performance.
KW - Chemical production scheduling
KW - Closed-loop solution
KW - Mixed-integer programming
KW - Rescheduling
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U2 - 10.1016/j.compchemeng.2016.08.006
DO - 10.1016/j.compchemeng.2016.08.006
M3 - Article
AN - SCOPUS:84984982147
SN - 0098-1354
VL - 94
SP - 312
EP - 330
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
ER -