Simulated moving bed multiobjective optimization using standing wave design and genetic algorithm

Abstract

in Wiley InterScience (www.interscience.wiley.com).Multiobjective optimization of simulated moving bed systems for chiral separations is studied by incorporating standing wave design into the nondominated sorting genetic algorithm with jumping genes. It allows simultaneous optimization of seven system and five operating parameters to show the trade-off between productivity, desorbent requirement (DR), and yield. If pressure limit, product purity, and yield are fixed, higher productivity can be obtained at a cost of higher DR. If yield is not fixed, it can be sacrificed to achieve higher productivity or vice versa. Short zones and high feed concentration favor high productivity, whereas long zones favor high yield and low DR. At fixed product purity and yield, increasing the pressure limit allows the use of smaller particles to increase productivity and to decrease DR. The performance of low-pressure simulated moving bed can be improved significantly by using shorter columns and smaller particles than those in conventional systems.

Experimental evaluation of the effect of a modified port‐location mode on the performance of a three‐zone simulated moving‐bed process for the separation of valine and isoleucine

“…The second prerequisite is to prepare a highly efficient and robust optimization tool that can produce the optimal operating parameters of the modified process. This tool was prepared in the present work on the basis of the nondominated sorting genetic algorithm with elitism and jumping genes (NSGA-II-JG) [20,21]. For the application of the prepared SMB optimization tool, the following two pieces of information are needed.…”

Simulated Moving Bed Chromatography: From Concept to Proof‐of‐Concept

“…Such optimization algorithms are, e.g., IPOPT (Interior Point OPTimizer) [185], employed for liquid as gas phase SMB separations [65,67,[186][187][188][189][190]; commercial package gOPT from gPROMS with a single (or multiple) shooting-control vector parameterization, used in the two-level optimization of an existing Parex® unit [181], for ageing analysis [191], gas phase separation of propane/propylene [117], or for optimal economic design [184]; MUSCOD-II, a software package based on a multiple shooting code [192]; nondominated sorting genetic algorithm (NSGA) or jumping gene-based algorithms [193], such as NSGA-II-JG, applied by several groups to optimize SMB units, from p-xylene to chiral separations [45,66,182,[194][195][196][197][198][199][200] Netherlands). Nevertheless, the design, construction, and operation of a flexible lab-scale SMB unit, the FlexSMB-LSRE®, as detailed elsewhere [37,201], is addressed in this section as an example of a chiral separation development until the demonstration stage (proof-of-concept).…”

Partial port-closing strategy for obtaining high throughput or high purities in a four-zone simulated moving bed chromatography for binary separation

“…Simulated moving bed (SMB) has been recognized as a highly efficient chromatographic process that was capable of continuous separation on a preparative or an industrial scale [1][2][3][4]. It has thus been of noteworthy applications in petrochemical, biochemical, and pharmaceutical industries [2,[5][6][7].…”

“…These four ports are moved periodically in the direction of the liquid-phase flow, which produces the effect of "simulated" counter-current movement of the adsorbent (solid phase) relative to the liquid phase. Such operation allows efficient use of the adsorbent and continuous processing of a feed mixture, leading to better performance than batch chromatographic processes [1][2][3][4].…”

“…Since these two performance criteria are of conflicting nature, the evaluation of throughput is usually carried out under a given purity requirement and the evaluation of product purity is carried out under a fixed throughput. To ensure high economical efficiency and meet the increasingly strengthened needs of product quality, it is important to operate the SMB process in such a way that higher throughput and higher purity can be achieved [4].…”