A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process

A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process

© Springer Science+Business Media Singapore 2016. The Shuffled Frog Leaping Algorithm (SFLA) is a population-based meta-heuristic algorithm which involves repeatedly updating the positions of frogs (solutions) in subgroup and shuffling frogs among subgroups to find the optimal solution. When updatin...

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Main Authors: Daoden K., Thaiupthump T.
Format: Book Series
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959084758&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42232
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-422322017-09-28T04:25:58Z A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process Daoden K. Thaiupthump T. © Springer Science+Business Media Singapore 2016. The Shuffled Frog Leaping Algorithm (SFLA) is a population-based meta-heuristic algorithm which involves repeatedly updating the positions of frogs (solutions) in subgroup and shuffling frogs among subgroups to find the optimal solution. When updating a frog’s position using the SFLA, the new position of a frog is equally likely to be at any point on a straight line between the current frog’s position and the better frog’s position. However, some parts of the line might be more beneficial to the global optimum solution exploration process. This paper investigates the use of a non-uniform distributed random number in updating frogs’ positions, to explore how such a modification affects the performance of the convergence to a global optimum solution, when compared to the original SFLA’s performance. 2017-09-28T04:25:58Z 2017-09-28T04:25:58Z 2016-01-01 Book Series 18761100 2-s2.0-84959084758 10.1007/978-981-10-0557-2_92 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959084758&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42232
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © Springer Science+Business Media Singapore 2016. The Shuffled Frog Leaping Algorithm (SFLA) is a population-based meta-heuristic algorithm which involves repeatedly updating the positions of frogs (solutions) in subgroup and shuffling frogs among subgroups to find the optimal solution. When updating a frog’s position using the SFLA, the new position of a frog is equally likely to be at any point on a straight line between the current frog’s position and the better frog’s position. However, some parts of the line might be more beneficial to the global optimum solution exploration process. This paper investigates the use of a non-uniform distributed random number in updating frogs’ positions, to explore how such a modification affects the performance of the convergence to a global optimum solution, when compared to the original SFLA’s performance.
format Book Series
author Daoden K.
Thaiupthump T.
spellingShingle Daoden K.
Thaiupthump T.
A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
author_facet Daoden K.
Thaiupthump T.
author_sort Daoden K.
title A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
title_short A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
title_full A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
title_fullStr A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
title_full_unstemmed A modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
title_sort modified shuffled frog leaping algorithm using truncated gaussian distribution in frog’s position updating process
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84959084758&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42232
_version_ 1681422150189187072

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