A comparative study of multi-objective optimization methodologies for molecular and process design
Author(s)
Lee, Lauren
Graham, Edward
Galindo, Amparo
Jackson, George
Adjiman, Claire
Type
Journal Article
Abstract
The need to consider multiple objectives in molecular design, whether based on techno-economic, environmental or health and safety metrics is increasingly recognized. There is, however, limited understanding of the suitability of different multi-objective optimization algorithm for the solution of such design problems. In this work, we present a systematic comparison of the performance of five mixed-integer non-linear programming (MINLP) multi-objective optimization algorithms on the selection of computer-aided molecular design (CAMD) and computer-aided molecular and process design (CAMPD) problems. The five methods are designed to address the discrete and nonlinear nature of the problem, with the aim of generating an accurate approximation of the Pareto front. They include: a weighted sum approach without global search phases (SWS), a weighted sum approach with simulated annealing (SA), a weighted sum approach with multi level single linkage (MLSL), the sandwich algorithm with MLSL and the non dominated sorting genetic algorithm-II (NSGA-II). The algorithms are compared systematically in two steps. The effectiveness of the global search methods is evaluated with SWS, WSSA and WSML. WSML is found to be most effective and a comparative analysis of WSML, SDML and NSGA-II is then undertaken. As a test set of these optimization techniques, two of CAMD and one CAMPD problems of varying dimensionality are formulated as case studies. The results show that the sandwich algorithm with MLSL provides the most efficient generation of a diverse set of Pareto points, leading to the construction of an approximate Pareto front close to exact Pareto front.
Date Issued
2020-05-08
Date Acceptance
2020-02-27
Citation
Computers and Chemical Engineering, 2020, 136
ISSN
0098-1354
Publisher
Elsevier
Journal / Book Title
Computers and Chemical Engineering
Volume
136
Copyright Statement
© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Engineering and Physical Sciences Research Council
Engineering & Physical Science Research Council (EPSRC)
Commission of the European Communities
Grant Number
EP/E016340/1
EP/J014958/1
EP/M507878/1
EP/J003840/1
727503
Subjects
Computer-aided molecular design
Computer-aided molecular and process design
Multi-objective optimization
Mixed-integer Nonlinear Programming
Global optimization
Publication Status
Published
Article Number
ARTN 106802
Date Publish Online
2020-02-29