Tim Janus scite author profile

Anhand von Simulationen mit einem kommerziellen Fließbildsimulator werden optimierte Fließbilder generiert. Da der Simulator keine expliziten Gleichungen und keine Ableitungen zur Verfügung stellt, wird ein memetischer Algorithmus eingesetzt. Dieser kombiniert einen evolutionären Algorithmus mit einer lokalen ableitungsfreien Suche. Es werden diskrete Designvariablen und kontinuierliche Parameter optimiert. Anhand eines Fallbeispiels wird das Verhalten des Optimierers demonstriert. Von Experten vorgeschlagene Startlösungen können deutlich verbessert werden, allerdings ist der Rechenzeitbedarf für komplexere Fließbilder noch relativ hoch.

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Neural Networks for Surrogate-assisted Evolutionary optimization of Chemical Processes

Janus

Luubbers

Engell

2020

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Optimization of a hydroformulation process in a thermomorphic solvent system using a commercial steady-state process simulator and a memetic algorithm

Janus

Cegla

Barkmann

et al. 2019

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Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis

Urselmann

Foussette²,

Janus

et al. 2016

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Tim Janus

Derivative-Free Chemical Process Synthesis by Memetic Algorithms Coupled to Aspen Plus Process Models

Optimization‐Based Process Synthesis Based on a Commercial Flowsheet Simulator

Neural Networks for Surrogate-assisted Evolutionary optimization of Chemical Processes

Optimization of a hydroformulation process in a thermomorphic solvent system using a commercial steady-state process simulator and a memetic algorithm

Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis

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