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Optimization of a True Moving Bed unit and determination of its feasible operating region using a novel Sliding Particle Swarm Optimization

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)368-381
Number of pages14
JournalCOMPUTERS AND INDUSTRIAL ENGINEERING
Volume135
DOIs
Publication statusPublished - 1 Sep 2019
Publication typeA1 Journal article-refereed

Abstract

The optimization of Simulated Moving Bed units has become an important topic to be developed in this field. The present work proposes a novel methodology to optimize a True Moving Bed unit and draw the feasible operating region through a novel improved Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying Acceleration Coefficients and Mutable Searching Region, here called Sliding Particle Swarm Optimization, concomitantly with an adapted method to define the feasible operating region. Two main contributions can be highlighted, first the process optimization with its feasible operational regions, leading to better results when compared with the numerical optimization based on the equilibrium theory, second a new particle swarm method is presented which can deal more efficiently with multi local minima problems. Finally, the concept of feasible operating region concept is presented as a support tool for the process operation. Three different operational scenarios were simulated here in order to verify the consistence and efficiency of the methodology. The main advantage of the methodology here proposed is the possibility to tracking all the possible operating regime of the unit while meeting a given process requirement.

ASJC Scopus subject areas

Keywords

  • Enantiomers separation, Feasible operating region, Particle Swarm Optimization, True Moving Bed

Publication forum classification

Field of science, Statistics Finland