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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IGI Global
2014
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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/ |
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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 |
13.250246 |