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Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach

Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy r...

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Main Authors:	Tan C.H., Yap K.S., Yap H.J.
Other Authors:	55175180600
Format:	Article
Published:	2023
Subjects:	Early activity duration estimation Expert judgment Fuzzy rules optimization Genetic algorithm Genetic fuzzy system Pittsburg approach Estimation Fuzzy logic Fuzzy rules Heuristic algorithms Knowledge based systems Linguistics Optimization Project management Activity duration Activity-based Binary encodings Execution time Fuzzy rule set Genetic fuzzy systems Heuristic search methods Interpretability Knowledge base Linguistic terms Similar degree Software project management Genetic algorithms
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id	my.uniten.dspace-30302
record_format	dspace
spelling	my.uniten.dspace-303022023-12-29T15:46:30Z Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach Tan C.H. Yap K.S. Yap H.J. 55175180600 24448864400 35319362200 Early activity duration estimation Expert judgment Fuzzy rules optimization Genetic algorithm Genetic fuzzy system Pittsburg approach Estimation Fuzzy logic Fuzzy rules Heuristic algorithms Knowledge based systems Linguistics Optimization Project management Activity duration Activity-based Binary encodings Execution time Expert judgment Fuzzy rule set Genetic fuzzy systems Heuristic search methods Interpretability Knowledge base Linguistic terms Pittsburg approach Similar degree Software project management Genetic algorithms Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation of early activity based duration estimation in software project management. The goal of the optimization is to reduce linguistic terms complexity and improve estimation accuracy of the fuzzy rule set while at the same time maintaining a similar degree of interpretability. The optimized numbers of linguistic terms in fuzzy rules by 27.76% using simplistic binary encoding mechanism managed to improve accuracy by 14.29% and reduce optimization execution time by 6.95% without compromising on interpretability in addition to promote improvement of knowledge base in fuzzy rule based systems. � 2012 Elsevier B.V. Final 2023-12-29T07:46:29Z 2023-12-29T07:46:29Z 2012 Article 10.1016/j.asoc.2012.03.018 2-s2.0-84861871169 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861871169&doi=10.1016%2fj.asoc.2012.03.018&partnerID=40&md5=758d0fe8e5928d79c9dc3e3115eaefcf https://irepository.uniten.edu.my/handle/123456789/30302 12 8 2168 2177 Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Early activity duration estimation Expert judgment Fuzzy rules optimization Genetic algorithm Genetic fuzzy system Pittsburg approach Estimation Fuzzy logic Fuzzy rules Heuristic algorithms Knowledge based systems Linguistics Optimization Project management Activity duration Activity-based Binary encodings Execution time Expert judgment Fuzzy rule set Genetic fuzzy systems Heuristic search methods Interpretability Knowledge base Linguistic terms Pittsburg approach Similar degree Software project management Genetic algorithms
spellingShingle	Early activity duration estimation Expert judgment Fuzzy rules optimization Genetic algorithm Genetic fuzzy system Pittsburg approach Estimation Fuzzy logic Fuzzy rules Heuristic algorithms Knowledge based systems Linguistics Optimization Project management Activity duration Activity-based Binary encodings Execution time Expert judgment Fuzzy rule set Genetic fuzzy systems Heuristic search methods Interpretability Knowledge base Linguistic terms Pittsburg approach Similar degree Software project management Genetic algorithms Tan C.H. Yap K.S. Yap H.J. Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
description	Genetic algorithm is well-known of its best heuristic search method. Fuzzy logic unveils the advantage of interpretability. Genetic fuzzy system exploits potential of optimization with ease of understanding that facilitates rules optimization. This paper presents the optimization of fourteen fuzzy rules for semi expert judgment automation of early activity based duration estimation in software project management. The goal of the optimization is to reduce linguistic terms complexity and improve estimation accuracy of the fuzzy rule set while at the same time maintaining a similar degree of interpretability. The optimized numbers of linguistic terms in fuzzy rules by 27.76% using simplistic binary encoding mechanism managed to improve accuracy by 14.29% and reduce optimization execution time by 6.95% without compromising on interpretability in addition to promote improvement of knowledge base in fuzzy rule based systems. � 2012 Elsevier B.V.
author2	55175180600
author_facet	55175180600 Tan C.H. Yap K.S. Yap H.J.
format	Article
author	Tan C.H. Yap K.S. Yap H.J.
author_sort	Tan C.H.
title	Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
title_short	Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
title_full	Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
title_fullStr	Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
title_full_unstemmed	Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
title_sort	application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using pittsburg approach
publishDate	2023
_version_	1806426616673337344
score	13.222552

Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach

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