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A Novel Back-Off Algorithm for the Integration Between Dynamic Optimization and Scheduling of Batch Processes Under Uncertainty
Abstract
This thesis presents a decomposition algorithm for obtaining robust scheduling and control decisions. It iteratively solves scheduling and dynamic optimization problems while approximating stochastic uncertainty through back-off terms, calculated through dynamic simulations of the process. This algorithm is compared, both in solution quality and performance, against a fully-integrated MINLP.
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Cite this version of the work
Yael Izamal Valdez Navarro
(2019).
A Novel Back-Off Algorithm for the Integration Between Dynamic Optimization and Scheduling of Batch Processes Under Uncertainty. UWSpace.
http://hdl.handle.net/10012/15276
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