Ganzheitliche Optimierung eines industriellen Batch‐Prozesses mit evolutionären Algorithmen

Zobel, T.; Groß, B.; Fieg, G.; Wozny, G.

doi:10.1002/cite.200650132

Chemie Ingenieur Technik

2006

DOI: 10.1002/cite.200650132

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Ganzheitliche Optimierung eines industriellen Batch‐Prozesses mit evolutionären Algorithmen

T. Zobel¹,

B. Groß²,

G. Fieg³

et al.

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Process Optimization of the Methanol Synthesis Using Different Local Optimization Algorithms

Sundberg

Rehfeldt

Peschel

et al. 2017

Chemie Ingenieur Technik

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Prozessoptimierung wird oft mit wenig flexibler Optimierungsfunktionalität in Prozesssimulatoren oder nach zeitintensiver Modellierung und Implementierung in algebraischen Modellierungssprachen durchgeführt. Der in dieser Arbeit angewandte hybride Ansatz nutzt Vorteile beider Methoden: MATLAB wird als Optimierungsplattform mit dem Prozesssimulator UniSim Design gekoppelt. Der Ansatz wird am Beispiel der industriellen Methanolsynthese evaluiert. Für die Optimierung werden gradientenbasierte und ableitungsfreie Algorithmen angewendet und so bestehende Arbeiten auf dem Gebiet sinnvoll ergänzt.

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Process Optimization of the Methanol Synthesis Using Different Local Optimization Algorithms

Sundberg

Rehfeldt

Peschel

et al. 2017

Chemie Ingenieur Technik

View full text Add to dashboard Cite

show abstract

A toolbox using the stochastic optimization algorithm MIPT and ChemCAD for the systematic process retrofit of complex chemical processes

Otte

Lorenz

Repke

2016

Computers & Chemical Engineering

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Ganzheitliche Optimierung eines industriellen Batch‐Prozesses mit evolutionären Algorithmen

Cited by 2 publications

References 0 publications

Process Optimization of the Methanol Synthesis Using Different Local Optimization Algorithms

Process Optimization of the Methanol Synthesis Using Different Local Optimization Algorithms

A toolbox using the stochastic optimization algorithm MIPT and ChemCAD for the systematic process retrofit of complex chemical processes

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