Adaptive Spiral Flying Sparrow Search Algorithm

Ouyang, Cheng; Qiu, Yaxian; Zhu, Donglin

doi:10.1155/2021/6505253

Cited by 37 publications

(22 citation statements)

References 21 publications

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“…The MATLAB-based source code for implementing this algorithm is available for registered users at https://www.mathworks.com/matlabcentral/ fileexchange/88788 (accessed on 1 December 2021). However, in [66,94], the authors proposed a variable spiral search technique for the followers to update their positions better. The position update equation of the followers using this search strategy is as follows:…”

Section: Sparrow Search Optimization Algorithmmentioning

confidence: 99%

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

et al. 2022

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This paper comprehensively reviews the spiral dynamics optimization (SDO) algorithm and investigates its characteristics. SDO algorithm is one of the most straightforward physics-based optimization algorithms and is successfully applied in various broad fields. This paper describes the recent advances of the SDO algorithm, including its adaptive, improved, and hybrid approaches. The growth of the SDO algorithm and its application in various areas, theoretical analysis, and comparison with its preceding and other algorithms are also described in detail. A detailed description of different spiral paths, their characteristics, and the application of these spiral approaches in developing and improving other optimization algorithms are comprehensively presented. The review concludes the current works on the SDO algorithm, highlighting its shortcomings and suggesting possible future research perspectives.

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Section: Sparrow Search Optimization Algorithmmentioning

confidence: 99%

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

et al. 2022

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“…This led researchers to modify SSA or hybridize it with other techniques to enhance its search space exploration and exploitation capabilities [ 17 – 20 ]. These changes are the modified SSA with six main modifications that include chaotic [ 21 , 22 ], random walk [ 12 , 23 ], discrete [ 24 , 25 ], adaptive [ 26 , 27 ], opposition-based learning [ 28 , 29 ], Lévy flight-based [ 30 , 31 ], and others [ 15 , 32 ]. More versions are introduced such as multi-objective SSA [ 33 , 34 ], and utilizing SSA as a component in other techniques (e.g., neural network [ 35 , 36 ] and support vector machine [ 37 , 38 ]).…”

Section: Introductionmentioning

confidence: 99%

Recent Versions and Applications of Sparrow Search Algorithm

Awadallah

Al-Betar

Doush

et al. 2023

Arch Computat Methods Eng

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This paper reviews the latest versions and applications of sparrow search algorithm (SSA). It is a recent swarm-based algorithm proposed in 2020 rapidly grew due to its simple and optimistic features. SSA is inspired by the sparrow living style of foraging and the anti-predation behavior of sparrows. Since its establishment, it has been utilized for a plethora of optimization problems in different research topics, such as mechanical engineering, electrical engineering, civil engineering, power systems, industrial engineering, image processing, networking, environment, robotics, planing and scheduling, and healthcare. Initially, the growth of SSA and its theoretical features are highlighted in terms of the number of published articles, citations, topics covered, etc. After that, the different extended versions of SSA are reviewed, where the main variations of SSA are produced to avoid premature convergence and to boost the diversity aspects. These extended versions are modifications and hybridization summarized with more focus on the motivations behind establishing these versions. Multi-objective SSA is also presented as another version to deal with Multi-objective optimization problems. The critical analysis of the main research gaps in the convergence behaviour of SSA is discussed. Finally, the conclusion and the possible future expansions are recommended based on the research works accomplished in the literature.

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“…For example, some studies [4,[18][19][20][21] combine two or more algorithms to improve the efficiency of solving optimization problems. (3) Improving the existing algorithms; the commonly used ones include chaotic maps [22,23], cellular [9,24], and mutation operators [25,26].…”

Section: Introductionmentioning

confidence: 99%

Porcellio scaber Algorithm with t-Distributed Elite Mutation for Global Optimization

Zhang

Yang

2022

Scientific Programming

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As the convergence accuracy of the Porcellio scaber algorithm (PSA) is low, this study proposes an improved algorithm based on the t-distribution elite mutation mechanism. First, the improved algorithm applies a t-distribution mutation to each dimension of the optimal solution of each generation. Using the dominant information of the optimal solution and t-distribution characteristics, the result of the mutation is then employed as the updated location of the selected porcellio; thus, the algorithm enhances the ability to jump out of local extreme values and improves the convergence speed. Second, the updated iterative rule of PSA may lead to the loss of information of the elite porcellio in the last generation. To solve this problem, the judgment mechanisms of the current and previous optimal solutions are included in the algorithm process. Finally, dynamic self-adaptive improvement is applied to the weight allocation parameters of PSA. Simulation results on 24 benchmark functions show that the improved algorithm has significant advantages in convergence accuracy, convergence speed, and stability when compared with basic PSA, PSO, GSA, and FPA. This indicates that the improved algorithm has certain advantages in terms of optimization. An optimal solution with good practicability is obtained by solving three practical engineering problems: three-bar truss, welded beam, and tension/compression-spring design.

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Adaptive Spiral Flying Sparrow Search Algorithm

Cited by 37 publications

References 21 publications

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

Recent Versions and Applications of Sparrow Search Algorithm

Porcellio scaber Algorithm with t-Distributed Elite Mutation for Global Optimization

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