Enhanced sparrow search algorithm based on improved game predatory mechanism and its application

• Published in: Digital signal processing Vol. 145; p. 104310
• Main Authors: Yang, Jiahui, Gao, Shesheng, Zhao, Xuehua, Li, Guo, Gao, Zhaohui
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2024
• Subjects: Elastic collision strategy; Game predatory mechanism; Sparrow search algorithm; VMD parameter optimization; Elastic collision strategy; VMD parameter optimization; Sparrow search algorithm; Game predatory mechanism
• ISSN: 1051-2004; 1095-4333
• DOI: 10.1016/j.dsp.2023.104310

In response to the problems of strong randomness in initialization, imperfect search mechanism and tendency to fall into local optimum when dealing with complex optimization problems by sparrow search algorithm (SSA), an enhanced sparrow search algorithm (ESSA) is proposed, which combines Hammersley low difference sequence (HLDS) and centroid opposition-based learning (COBL), improved game predatory mechanism (GPM) and elastic collision strategy (EC). The ESSA can improve the initial individual quality, and avoid the attraction of local optima. In addition, the ESSA can effectively improve the search mechanism by increasing information exchange of individuals and balancing global search and local development. The effectiveness of ESSA is verified through simulation experiments of benchmark functions and variational modal decomposition (VMD) parameter optimization.