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Detalle de: Dynamic optimization of single- and multi-stage systems using a hybrid Stochastic-deterministic method

Title Dynamic optimization of single- and multi-stage systems using a hybrid Stochastic-deterministic method
Abstract

A hybrid stochastic−deterministic method, based on the control vector parameterization (CVP) approach, is presented as a reliable and efficient alternative for the solution of dynamic optimization (or open loop optimal control) problems.The problems under consideration are related to free final time single-stage systems and more general multi-stage procecesses that are described by different sets of differential and algebraic equations (DAEs), one for each stage. The operating conditions and the duration of each stage must be computed in order to achieve an overall optimal result for the process subject to constraints in the state and control variables. The solution of three challenging dynamic optimization problems is presented, including a large-scale case study, showing the capabilities of this new strategy.

Apa Reference Balsa-Canto, E., Vassiliadis, V. S., & Banga, J. R. (2005). Dynamic Optimization of Single- and Multi-Stage Systems Using a Hybrid Stochastic−Deterministic Method. Industrial & Engineering Chemistry Research, 44(5), 1514–1523. 10.1021/ie0493659
Doi 10.1021/IE0493659
Publication Date 27 Jan 2005
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Biosystems Modeling
Research Groups Computational Biology Lab at MBG
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