caa a22 4500 605469105 CHVBK 20210128100320.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1388-4 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1388-4 The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review [Elektronische Daten] [Arezoo Sarkheyli, Azlan Zain, Safian Sharif] 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. Springer-Verlag Berlin Heidelberg, 2014 Shuffled frog leaping algorithm nationallicence Optimization nationallicence Modification nationallicence Hybridization nationallicence Application nationallicence Comparison nationallicence Review nationallicence Sarkheyli Arezoo Soft Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut Zain Azlan Soft Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut Sharif Safian Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 2011-2038 1432-7643 19:7<2011 2015 19 500 https://doi.org/10.1007/s00500-014-1388-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1388-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sarkheyli Arezoo Soft Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut NATIONALLICENCE 700 1- Zain Azlan Soft Computing Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut NATIONALLICENCE 700 1- Sharif Safian Department of Manufacturing and Industrial Engineering, Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310, UTM Skudai, Johor, Malaysia aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 2011-2038 1432-7643 19:7<2011 2015 19 500