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Soft Computing

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01.07.2015 | Methodologies and Application

The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review

verfasst von: Arezoo Sarkheyli, Azlan Mohd Zain, Safian Sharif

Erschienen in: Soft Computing | Ausgabe 7/2015

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Abstract

Shuffled frog leaping algorithm (SFLA) is a meta-heuristic to handle different large-scale optimization problems. SFLA is a population-based algorithm that combines the advantages of memetic algorithm and particle swarm optimization. This paper compares previous researches on SFLA and its effectiveness, with the most applied optimization algorithms reviewed and analyzed. Based on the literature, many efforts by previous researchers on SFLA denote the next generations of basic SFLA with diverse structures for modified SFLA or hybrid SFLA. As well, an attempt is made to highlight these structures, their enhancements and advantages. Moreover, this paper considers top improvements on SFLA for solving multi-objective optimization problems, enhancing local and global exploration, avoiding being trapped into local optima, declining computational time and improving the quality of the initial population. The measured enhancements in SFLA are based on the statistical results obtained from 89 published papers and by considering the most common and effective modifications done by a large number of researchers. Finally, the quantitative validations address the SFLA as a robust algorithm employed in various applications which outperforms the other optimization algorithms.

Vorheriger Artikel Complement information entropy for uncertainty measure in fuzzy rough set and its applications

Nächster Artikel Adaptive self-tuning techniques for performance tuning of database systems: a fuzzy-based approach with tuning moderation

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Titel: The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review
verfasst von: Arezoo Sarkheyli
Azlan Mohd Zain
Safian Sharif
Publikationsdatum: 01.07.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 7/2015
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1388-4

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