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Reseach Article

An Efficient Modified Shuffled Frog Leaping Optimization Algorithm

by Mohammad Pourmahmood Aghababa, Mohammd Esmaeel Akbari, Amin Mohammadpour Shotorbani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 1
Year of Publication: 2011
Authors: Mohammad Pourmahmood Aghababa, Mohammd Esmaeel Akbari, Amin Mohammadpour Shotorbani
10.5120/3870-5406

Mohammad Pourmahmood Aghababa, Mohammd Esmaeel Akbari, Amin Mohammadpour Shotorbani . An Efficient Modified Shuffled Frog Leaping Optimization Algorithm. International Journal of Computer Applications. 32, 1 ( October 2011), 26-30. DOI=10.5120/3870-5406

@article{ 10.5120/3870-5406,
author = { Mohammad Pourmahmood Aghababa, Mohammd Esmaeel Akbari, Amin Mohammadpour Shotorbani },
title = { An Efficient Modified Shuffled Frog Leaping Optimization Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 1 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number1/3870-5406/ },
doi = { 10.5120/3870-5406 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:02.655634+05:30
%A Mohammad Pourmahmood Aghababa
%A Mohammd Esmaeel Akbari
%A Amin Mohammadpour Shotorbani
%T An Efficient Modified Shuffled Frog Leaping Optimization Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 1
%P 26-30
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a modified shuffled frog leaping (MSFL) algorithm is proposed to overcome drawbacks of standard shuffled frog leaping (SFL) method. The MSFL approach is based on two major modifications on the conventional SFL method: (1) an adaptive accelerated position changing of frogs and (2) sweeping between randomly selected frogs (called superseding frogs). The first modification causes a fast convergence rate and consequently achieving a rapid adaptive algorithm, while the second one causes a better diversification and consequently escaping from local optimum traps. The MSFL algorithm performance is validated using benchmark functions. Simulation results indicate the superiority of MSFL to that of the original SFL in terms of optimal precision and fast convergence rate.

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Index Terms

Computer Science
Information Sciences

Keywords

Shuffled frog leaping algorithm Optimization approach Convergence rate Escaping local optimum