Paper
6 May 2022 Improved sparrow search algorithm combining adaptive mutation and proportion adjustment strategy
Hualiang Wang, Shaoming Qiu, Haitao Mi, Ao Li
Author Affiliations +
Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 1217604 (2022) https://doi.org/10.1117/12.2636425
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China
Abstract
Aiming at the problems of low optimization accuracy, slow convergence speed and easy to fall into local optimization of sparrow algorithm, an improved sparrow search algorithm combining adaptive mutation and proportion adjustment strategy(AISSA) is proposed. Firstly, the nonlinear decreasing inertia weight is used to adjust the global and local search ability of SSA. Secondly, the producer-scrounger proportion adjustment strategy is introduced to adjust the proportion of producers and scrounger in the iterative process, so as to improve the optimization accuracy and convergence speed of the algorithm. Finally, Tent chaotic mutation and adaptive t-distribution mutation are carried out for individuals with different fitness values to improve the local optimization ability of SSA and speed up the convergence. The final results show that AISSA has higher optimization accuracy and better stability than SSA.
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Hualiang Wang, Shaoming Qiu, Haitao Mi, and Ao Li "Improved sparrow search algorithm combining adaptive mutation and proportion adjustment strategy", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 1217604 (6 May 2022); https://doi.org/10.1117/12.2636425
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KEYWORDS
Optimization (mathematics)

Computer simulations

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