Cuckoo Search Optimization and Application to Liquid–Liquid Equilibrium

Authored by: Anand Bharti , Debashis Kundu , Dharamashi Rabari , Tamal Banerjee

Phase Equilibria in Ionic Liquid Facilitated Liquid–Liquid Extractions

Print publication date:  March  2017
Online publication date:  March  2017

Print ISBN: 9781498769488
eBook ISBN: 9781315367163
Adobe ISBN:

10.1201/9781315367163-7

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Abstract

This chapter uses a new variant of the optimization technique, namely Cuckoo Search (CS) algorithm, to generate the liquid–liquid equilibrium (LLE) data. Liquid–liquid extraction is an important separation technology with a wide range of applications in chemical, petrochemical and pharmaceutical industries. The LLE data of multi-component systems are essential for proper understanding of the extraction process and for the designing and optimization of separation processes. Excess Gibbs free energy models, such as the nonrandom two-liquid (NRTL; Renon & Prausnitz, 1968) and the UNIversal QUAsiChemical (UNIQUAC; Abrams & Prausnitz, 1975) models, are commonly used to predict the LLE as they provide good agreement with experimental data (Banerjee, Singh, Sahoo, & Khanna, 2005; Santiago, Santos, & Aznar, 2009; Vatani, Asghari, & Vakili-Nezhaad, 2012). For LLE prediction, each of these models requires binary interaction parameters. These parameters are generally estimated from the known experimental LLE data by the optimization of an objective function. Mathematically, the aim of optimization is to find the set of inputs that either maximizes or minimizes the output of the objective function. In LLE modelling, the objective function is nonlinear and highly nonconvex having multiple local optima which makes most conventional methods (deterministic algorithms) inefficient and stuck in the wrong solutions. For the correct LLE prediction in liquid–liquid phase equilibria, finding the global optimum (reliable interaction parameters) thus becomes a necessary requirement.

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