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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

Many industrial problems in process optimization are Multi-Objective (MO), where each of the objectives represents different facets of the issue. Thus, having in hand multiple solutions prior to selecting the best solution is a seminal advantage. In this chapter, the weighted sum scalarization appro...

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Main Authors: Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.
Format: Book
Published: IGI Global 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949844929&doi=10.4018%2f978-1-4666-6252-0.ch017&partnerID=40&md5=c6f2075cff4cc866690718a62e6ae87b
http://eprints.utp.edu.my/31258/
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spelling my.utp.eprints.312582022-03-25T09:04:37Z Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution Ganesan, T. Elamvazuthi, I. Shaari, K.Z.K. Vasant, P. Many industrial problems in process optimization are Multi-Objective (MO), where each of the objectives represents different facets of the issue. Thus, having in hand multiple solutions prior to selecting the best solution is a seminal advantage. In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). These methods are then employed to trace the approximate Pareto frontier to the bioethanol production problem. The Hypervolume Indicator (HVI) is applied to gauge the capabilities of each algorithm in approximating the Pareto frontier. Some comparative studies are then carried out with the algorithms developed in this chapter. Analysis on the performance as well as the quality of the solutions obtained by these algorithms is shown here. © 2014, IGI Global. IGI Global 2014 Book NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949844929&doi=10.4018%2f978-1-4666-6252-0.ch017&partnerID=40&md5=c6f2075cff4cc866690718a62e6ae87b Ganesan, T. and Elamvazuthi, I. and Shaari, K.Z.K. and Vasant, P. (2014) Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution. IGI Global, pp. 340-359. http://eprints.utp.edu.my/31258/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Many industrial problems in process optimization are Multi-Objective (MO), where each of the objectives represents different facets of the issue. Thus, having in hand multiple solutions prior to selecting the best solution is a seminal advantage. In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). These methods are then employed to trace the approximate Pareto frontier to the bioethanol production problem. The Hypervolume Indicator (HVI) is applied to gauge the capabilities of each algorithm in approximating the Pareto frontier. Some comparative studies are then carried out with the algorithms developed in this chapter. Analysis on the performance as well as the quality of the solutions obtained by these algorithms is shown here. © 2014, IGI Global.
format Book
author Ganesan, T.
Elamvazuthi, I.
Shaari, K.Z.K.
Vasant, P.
spellingShingle Ganesan, T.
Elamvazuthi, I.
Shaari, K.Z.K.
Vasant, P.
Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
author_facet Ganesan, T.
Elamvazuthi, I.
Shaari, K.Z.K.
Vasant, P.
author_sort Ganesan, T.
title Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
title_short Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
title_full Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
title_fullStr Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
title_full_unstemmed Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
title_sort multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
publisher IGI Global
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949844929&doi=10.4018%2f978-1-4666-6252-0.ch017&partnerID=40&md5=c6f2075cff4cc866690718a62e6ae87b
http://eprints.utp.edu.my/31258/
_version_ 1738657222551928832
score 13.211869

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