Publication: Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach
Date
2012
Authors
Tan C.H.
Yap K.S.
Yap H.J.
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Abstract
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.
Description
Keywords
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