Makale detayı · 2022
Chaotic Harris hawks optimization algorithm
- Yıl
- 2022
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Journal of Computational Design and Engineering
- Katalog eşleşmesi (ISSN) Journal of Computational Design and Engineering
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Abstract Harris hawks optimization (HHO) is a population-based metaheuristic algorithm, inspired by the hunting strategy and cooperative behavior of Harris hawks. In this study, HHO is hybridized with 10 different chaotic maps to adjust its critical parameters. Hybridization is performed using four different methods. First, 15 test functions with unimodal and multimodal features are used for the analysis to determine the most successful chaotic map and the hybridization method. The results obtained reveal that chaotic maps increase the performance of HHO and show that the piecewise map method is the most effective one. Moreover, the proposed chaotic HHO is compared to four metaheuristic algorithms in the literature using the CEC2019 set. Next, the proposed chaotic HHO is applied to three mechanical design problems, including pressure vessel, tension/compression spring, and three-bar truss system as benchmarks. The performances and results are compared with other popular algorithms in the literature. They show that the proposed chaotic HHO algorithm can compete with HHO and other algorithms on solving the given engineering problems very successfully.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
72 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 9 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- Chaotic marine predators algorithm for global optimization of real-world engineering problems 2023
- A novel chaotic Runge Kutta optimization algorithm for solving constrained engineering problems 2022
- Chaotic Sand Cat Swarm Optimization 2023
- Chaotic Sand Cat Swarm Optimization 2023
- A modified starfish optimization algorithm (M-SFOA) for global optimization problems and its application to heart disease risk prediction 2026
- An improved Harris Hawks Optimization algorithm for continuous and discrete optimization problems 2022
- An improved Harris Hawks Optimization algorithm for continuous and discrete optimization problems 2022
- Dynamic random walk-based sled dog optimization algorithm and artificial neural network for optimizing design engineering problems 2025
- A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems 2025