The optimization of cyclic adsorption processes is a challenging task, and has aroused interest in the context of optimizing CO2 capture processes, where the optimization problem typically involves conflicting objectives, such as energy demand and productivity, and nonlinear constraints which enforce the separation targets. In this contribution we propose a revised version of the multilevel coordinate search algorithm, which can cope with nonlinear constraints and multiple objectives. The algorithm is tested for two different temperature swing adsorption cycles and computational results show that MO-MCS performs better than several publicly available multi-objective methods.

MO-MCS: An Efficient Multi-objective Optimization Algorithm for the Optimization of Temperature/Pressure Swing Adsorption Cycles

CAPRA, FEDERICO;MARTELLI, EMANUELE
2016

Abstract

The optimization of cyclic adsorption processes is a challenging task, and has aroused interest in the context of optimizing CO2 capture processes, where the optimization problem typically involves conflicting objectives, such as energy demand and productivity, and nonlinear constraints which enforce the separation targets. In this contribution we propose a revised version of the multilevel coordinate search algorithm, which can cope with nonlinear constraints and multiple objectives. The algorithm is tested for two different temperature swing adsorption cycles and computational results show that MO-MCS performs better than several publicly available multi-objective methods.
26TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING (ESCAPE), PT B
9780444634283
black-box; CO2 capture; Multi-objective; temperature swing adsorption; Chemical Engineering (all); Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1015360
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