Efficient ant colony optimization for computer aided molecular design: Case study solvent selection problem

• Published in: Computers & chemical engineering Vol. 78; no. C; pp. 1 - 9
• Main Authors: Gebreslassie, Berhane H., Diwekar, Urmila M.
• Format: Journal Article
• Language: English
• Published: United Kingdom Elsevier Ltd 01.07.2015; Elsevier
• Subjects: Algorithms; Ant colony optimization; Computer aided design; Computer aided molecular design; Group contribution method; Hammersley sequence sampling; Liquid-liquid extraction; Methodology; Optimization; Oracle penalty function; Sampling; Solvents; UNIFAC; Hammersley sequence sampling; Group contribution method; Ant colony optimization; UNIFAC; Oracle penalty function; Computer aided molecular design
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2015.04.004

•An industrial case study.•First application of ant colony optimization to solvent selection problem.•Better results for solvent selection as compared to earlier methods.•Computationally efficient framework. In this paper, we propose a novel computer-aided molecular design (CAMD) methodology for the design of optimal solvents based on an efficient ant colony optimization (EACO) algorithm. The molecular design problem is formulated as a mixed integer nonlinear programming (MINLP) model in which a solvent performance measure is maximized (solute distribution coefficient) subject to structural feasibility, property, and process constraints. In developing the EACO algorithm, the better uniformity property of Hammersley sequence sampling (HSS) is exploited. The capabilities of the proposed methodology are illustrated using a real world case study for the design of an optimal solvent for extraction of acetic acid from waste process stream using liquid–liquid extraction. The UNIFAC model based on the infinite dilution activity coefficient is used to estimate the mixture properties. New solvents with better targeted properties are proposed.