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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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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
score 13.214268

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