Normative Fish Swarm Algorithm For Global Optimization With Applications

Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work...

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Main Author:	Tan, Weng Hooi
Format:	Thesis
Language:	English
Published:	2019
Subjects:	T Technology
Online Access:	http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf
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id	my-usm-ep.48568
record_format	uketd_dc
spelling	my-usm-ep.485682021-11-17T03:42:10Z Normative Fish Swarm Algorithm For Global Optimization With Applications 2019-12-01 Tan, Weng Hooi T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work proposes a viable local and global seeking strategy to achieve compelling global optimum at predominant convergence rate. Referred to as Normative Fish Swarm Algorithm (NFSA), the proposed Fish Swarm Algorithm, Optimized by Particle Swarm Optimization with Extended Memory (PSOEM-FSA) is expanded by amalgamating the normative knowledge to provide supplementary guidelines for better global optimum achievement and convergence rate. NFSA incorporates adjustments of visual, visualmin, step and stepmin parameters to adjust the inconsistency between the prospection and exploitation. In addition, the technique of modified global crossover is incorporated to strengthen the relationship between the candidate solutions. The performance of the NFSA has been tested on ten benchmark functions. The obtained results demonstrated that NFSA accomplished predominant outcomes in terms of optimized solution and convergence speed. Besides that, NFSA has been applied on multi-objective optimization and Maximum Power Point Tracking (MPPT) problems. The results obtained from both applications have proved that the proposed NFSA is more effective in multi-objective optimization and MPPT approaches in comparison to few compared evolutionary algorithms. 2019-12 Thesis http://eprints.usm.my/48568/ http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology Tan, Weng Hooi Normative Fish Swarm Algorithm For Global Optimization With Applications
description	Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. Therefore, this work proposes a viable local and global seeking strategy to achieve compelling global optimum at predominant convergence rate. Referred to as Normative Fish Swarm Algorithm (NFSA), the proposed Fish Swarm Algorithm, Optimized by Particle Swarm Optimization with Extended Memory (PSOEM-FSA) is expanded by amalgamating the normative knowledge to provide supplementary guidelines for better global optimum achievement and convergence rate. NFSA incorporates adjustments of visual, visualmin, step and stepmin parameters to adjust the inconsistency between the prospection and exploitation. In addition, the technique of modified global crossover is incorporated to strengthen the relationship between the candidate solutions. The performance of the NFSA has been tested on ten benchmark functions. The obtained results demonstrated that NFSA accomplished predominant outcomes in terms of optimized solution and convergence speed. Besides that, NFSA has been applied on multi-objective optimization and Maximum Power Point Tracking (MPPT) problems. The results obtained from both applications have proved that the proposed NFSA is more effective in multi-objective optimization and MPPT approaches in comparison to few compared evolutionary algorithms.
format	Thesis
qualification_level	Master's degree
author	Tan, Weng Hooi
author_facet	Tan, Weng Hooi
author_sort	Tan, Weng Hooi
title	Normative Fish Swarm Algorithm For Global Optimization With Applications
title_short	Normative Fish Swarm Algorithm For Global Optimization With Applications
title_full	Normative Fish Swarm Algorithm For Global Optimization With Applications
title_fullStr	Normative Fish Swarm Algorithm For Global Optimization With Applications
title_full_unstemmed	Normative Fish Swarm Algorithm For Global Optimization With Applications
title_sort	normative fish swarm algorithm for global optimization with applications
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2019
url	http://eprints.usm.my/48568/1/Normative%20Fish%20Swarm%20Algorithm%20For%20Global%20Optimization%20With%20Applications.pdf
_version_	1747821948444868608

Normative Fish Swarm Algorithm For Global Optimization With Applications

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