Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread algorithms. It was developed by Eusuff and Lansey in 2006. SFLA is a population-based metaheuristic algorithm that combines the benefits of memetics with particle swarm optimization. It has been used in various areas, especially in engineering problems due to its implementation easiness and limited variables. Many improvements have been made to the algorithm to alleviate its drawbacks, whether they were achieved through modifications or hybridizations with other well-known algorithms. This paper reviews the most relevant works on this algorithm. An overview of the SFLA is first conducted, followed by the algorithm's most recent modifications and hybridizations. Next, recent applications of the algorithm are discussed. Then, an operational framework of SLFA and its variants is proposed to analyze their uses on different cohorts of applications. Finally, future improvements to the algorithm are suggested. The main incentive to conduct this survey to provide useful information about the SFLA to researchers interested in working on the algorithm's enhancement or application.
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Electric energy is accounted as one of the major goods in human life, and also have a great role in progressing and developing the several sectors as economics, manufactures and any other sector related to daily use. In this study the monthly demand of electricity in Sulaimani governorate have been used, the main goal of the study is to choose appropriate model to forecast the monthly demand of electric in Sulaimani governorate for 12 months in 2020, the analyzing,results and comparison shows that FSARIMA(0,0,0)x(2,1,0) 4 is appropriate model
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