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Erschienen in: Engineering with Computers 2/2023

21.11.2022 | Original Article

An enhanced hybrid seagull optimization algorithm with its application in engineering optimization

verfasst von: Gang Hu, Jiao Wang, Yan Li, MingShun Yang, Jiaoyue Zheng

Erschienen in: Engineering with Computers | Ausgabe 2/2023

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Abstract

Aiming at the problems such as slow search speed, low optimization accuracy, and premature convergence of standard seagull optimization algorithm, an enhanced hybrid strategy seagull optimization algorithm was proposed. First, chaos mapping is used to generate the initial population to increase the diversity of the population, which lays the foundation for the global search. Then, a nonlinear convergence parameter and inertia weight are introduced to improve the convergence factor and to balance the global exploration and local development of the algorithm, so as to accelerate the convergence speed. Finally, an imitation crossover mutation strategy is introduced to avoid premature convergence of the algorithm. Comparison and verification between MSSOA and its incomplete algorithms are better than SOA, indicating that each improvement is effective and its incomplete algorithms all improve SOA to different degrees in both exploration and exploitation. 25 classic functions and the CEC2014 benchmark functions were tested, and compared with seven well-known meta-heuristic algorithms and its improved algorithm to evaluate the validity of the algorithm. The algorithm can explore different regions of the search space, avoid local optimum and converge to global optimum. Compared with other algorithms, the results of non-parametric statistical analysis and performance index show that the enhanced algorithm in this paper has better comprehensive optimization performance, significantly improves the search speed and convergence precision, and has strong ability to get rid of the local optimal solution. At the same time, in order to prove its applicability and feasibility, it is used to solve two constrained mechanical engineering design problems contain the interpolation curve engineering design and the aircraft wing design. The engineering curve shape with minimum energy, minimum curvature, and the smoother shape of airfoil with low drag are obtained. It is proved that enhanced algorithm in this paper can solve practical problems with constrained and unknown search space highly effectively.

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Metadaten
Titel
An enhanced hybrid seagull optimization algorithm with its application in engineering optimization
verfasst von
Gang Hu
Jiao Wang
Yan Li
MingShun Yang
Jiaoyue Zheng
Publikationsdatum
21.11.2022
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 2/2023
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-022-01746-y

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