Fuzzy lifetime in genetic algorithm against premature convergence

1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010 organized by Universiti Malaysia Perlis (UniMAP) and co-organized by Universiti Sains Malaysia (USM) & Universiti Kebangsaan Malaysia (UKM), 2nd - 3rd June 2010 at Eastern & Oriental Hotel, Penang.

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Bibliographic Details
Main Authors:	Mohammad Jalali, Varnamkhasti, Lai, Soon Lee, Mohd Rizam, Abu Bakar, Nawfal, A. Mehdy
Other Authors:	jalali@inspem.upm.edu.my
Format:	Working Paper
Language:	English
Published:	Universiti Malaysia Perlis (UniMAP) 2010
Subjects:	Fuzzy lifetime Genetic algorithm (GA) Premature convergence Regional Conference on Applied and Engineering Mathematics (RCAEM)
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/10315
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-10315
record_format	dspace
spelling	my.unimap-103152016-06-12T14:29:21Z Fuzzy lifetime in genetic algorithm against premature convergence Mohammad Jalali, Varnamkhasti Lai, Soon Lee Mohd Rizam, Abu Bakar Nawfal, A. Mehdy jalali@inspem.upm.edu.my Lee@math.upm.edu.my rizam@math.upm.edu.my nawfal.upm@hotmail.com Fuzzy lifetime Genetic algorithm (GA) Premature convergence Regional Conference on Applied and Engineering Mathematics (RCAEM) 1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010 organized by Universiti Malaysia Perlis (UniMAP) and co-organized by Universiti Sains Malaysia (USM) & Universiti Kebangsaan Malaysia (UKM), 2nd - 3rd June 2010 at Eastern & Oriental Hotel, Penang. A large scale of design, control, scheduling or other engineering problems results in solution of optimization problems. In numerous areas of engineering there are problems to which Genetic Algorithms (GAs) can without difficulty be applied. Premature convergence is a classical problem in finding optimal solution in Genetic Algorithms. Varying the population size and the population diversity are the two possible ways of avoiding the premature convergence in a GA. If the population size is small, the diversity of population may be small and the GA will converge very quickly. On the other hand, if the population size is too big, the GA will take a lot of time to converge and this may cause wastage in computational resources. In this paper, we propose a Fuzzy Genetic Algorithm (FGA) which uses a new technique that is based on the lifetime for each chromosome. We use a conceptual of distance from the best chromosome in a population to create a fuzzy membership function which formed a new fitness function for the FGA. This new fitness function will then be used in a bi-linear allocation lifetime for varying the population size. Computational experiments are conducted to compare the performance of this new technique with some commonly used selection mechanisms found in a standard GA for solving some numerical functions from the literature. 2010-11-26T01:36:03Z 2010-11-26T01:36:03Z 2010-06-02 Working Paper Vol.5(3), p.465-468 http://hdl.handle.net/123456789/10315 en Proceedings of the 1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010 Universiti Malaysia Perlis (UniMAP) Institut Matematik Kejuruteraan
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Fuzzy lifetime Genetic algorithm (GA) Premature convergence Regional Conference on Applied and Engineering Mathematics (RCAEM)
spellingShingle	Fuzzy lifetime Genetic algorithm (GA) Premature convergence Regional Conference on Applied and Engineering Mathematics (RCAEM) Mohammad Jalali, Varnamkhasti Lai, Soon Lee Mohd Rizam, Abu Bakar Nawfal, A. Mehdy Fuzzy lifetime in genetic algorithm against premature convergence
description	1st Regional Conference on Applied and Engineering Mathematics (RCAEM-I) 2010 organized by Universiti Malaysia Perlis (UniMAP) and co-organized by Universiti Sains Malaysia (USM) & Universiti Kebangsaan Malaysia (UKM), 2nd - 3rd June 2010 at Eastern & Oriental Hotel, Penang.
author2	jalali@inspem.upm.edu.my
author_facet	jalali@inspem.upm.edu.my Mohammad Jalali, Varnamkhasti Lai, Soon Lee Mohd Rizam, Abu Bakar Nawfal, A. Mehdy
format	Working Paper
author	Mohammad Jalali, Varnamkhasti Lai, Soon Lee Mohd Rizam, Abu Bakar Nawfal, A. Mehdy
author_sort	Mohammad Jalali, Varnamkhasti
title	Fuzzy lifetime in genetic algorithm against premature convergence
title_short	Fuzzy lifetime in genetic algorithm against premature convergence
title_full	Fuzzy lifetime in genetic algorithm against premature convergence
title_fullStr	Fuzzy lifetime in genetic algorithm against premature convergence
title_full_unstemmed	Fuzzy lifetime in genetic algorithm against premature convergence
title_sort	fuzzy lifetime in genetic algorithm against premature convergence
publisher	Universiti Malaysia Perlis (UniMAP)
publishDate	2010
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/10315
_version_	1643789809811980288

Fuzzy lifetime in genetic algorithm against premature convergence

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