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An Improved Future Search Algorithm Based on the Sine Cosine Algorithm for Function Optimization Problems
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DOI：10.1109/ACCESS.2023.3258970.png)
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Abstract
En 中文
Future search algorithm imitates the person living life. If one person finds that his life is not good, he will try to change his living life, and he will imitate a more successful person. To overcome insufficient performances of the basic Future search algorithm, this paper proposed an improved Future search algorithm based on the sine cosine algorithm (FSASCA). The proposed algorithm uses sine cosine algorithm to loop-progressive find the best solution. The searching method of the sine cosine algorithm can make the feasible solution to be re-positioned around another feasible solutions, which can make the proposed algorithm have a strong exploitation ability. Four coefficient factors are added in the basic FSA, and new update methods are introduced in the searching phase. To verify the searching and optimization performances of the proposed algorithm in this paper, this paper also gives data calculation results, Wilcoxon rank sum test, iteration figures, box plot figures, and searching path figures. Experimental results showed that FSASCA has a better iteration speed, the convergence precision, the solving accuracy, the strong competitive, and the high balance.
Keywords:
Optimization
Mathematical models
Optimization methods
Convergence
Search problems
Statistics
Sociology
Future search algorithm
sine cosine algorithm
optimization problem
function optimization
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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