Your browser doesn't support javascript.
loading
A multi-strategy improved rime optimization algorithm for three-dimensional USV path planning and global optimization.
Gu, Gaoquan; Lou, Jingjun; Wan, Haibo.
Afiliação
  • Gu G; College of Naval Architecture and Ocean Engineering, Naval University of Engineering, Wuhan, 430033, Hubei, China.
  • Lou J; College of Naval Architecture and Ocean Engineering, Naval University of Engineering, Wuhan, 430033, Hubei, China. loujingjun760525@163.com.
  • Wan H; College of Naval Architecture and Ocean Engineering, Naval University of Engineering, Wuhan, 430033, Hubei, China.
Sci Rep ; 14(1): 12603, 2024 Jun 01.
Article em En | MEDLINE | ID: mdl-38824256
ABSTRACT
The RIME optimization algorithm (RIME) represents an advanced optimization technique. However, it suffers from issues such as slow convergence speed and susceptibility to falling into local optima. In response to these shortcomings, we propose a multi-strategy enhanced version known as the multi-strategy improved RIME optimization algorithm (MIRIME). Firstly, the Tent chaotic map is utilized to initialize the population, laying the groundwork for global optimization. Secondly, we introduce an adaptive update strategy based on leadership and the dynamic centroid, facilitating the swarm's exploitation in a more favorable direction. To address the problem of population scarcity in later iterations, the lens imaging opposition-based learning control strategy is introduced to enhance population diversity and ensure convergence accuracy. The proposed centroid boundary control strategy not only limits the search boundaries of individuals but also effectively enhances the algorithm's search focus and efficiency. Finally, to demonstrate the performance of MIRIME, we employ CEC 2017 and CEC 2022 test suites to compare it with 11 popular algorithms across different dimensions, verifying its effectiveness. Additionally, to assess the method's practical feasibility, we apply MIRIME to solve the three-dimensional path planning problem for unmanned surface vehicles. Experimental results indicate that MIRIME outperforms other competing algorithms in terms of solution quality and stability, highlighting its superior application potential.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido