Improved Sparrow Algorithm Based on Game Predatory Mechanism and Suicide Mechanism

• Published in: Computational intelligence and neuroscience 2022-05, Vol.2022, p.4925416-23
• Main Authors: Yang, Ping, Yan, Shaoqiang, Zhu, Donglin, Wang, Jiangpeng, Wu, Fengxuan, Yan, Zhe, Yan, Song
• Format: Article
• Language: English
• Subjects: Algorithms; Competitiveness; Convergence; Food; Foraging behavior; Game theory; Hunger; Intelligence; Local optimization; Optimization algorithms; Path planning; Population; Review; Search algorithms; Search process; Suicide; Unmanned aerial vehicles
• ISSN: 1687-5265; 1687-5273
• DOI: 10.1155/2022/4925416

In order to overcome the defect that sparrow search algorithm converges very fast but is easy to fall into the trap of local optimization, based on the original mechanism of sparrow algorithm, this paper proposes game predatory mechanism and suicide mechanism, which makes sparrow algorithm more in line with its biological characteristics and enhances the ability of the algorithm to get rid of the attraction of local optimization while retaining the advantages of fast convergence speed. By initializing the population with the good point set strategy, the quality of the initial population is guaranteed and the diversity of the population is enhanced. In view of the current situation that the diversity index evaluation does not consider the invalid search caused by individuals beyond the boundary in the search process, an index to measure the invalid search beyond the boundary in the search process is proposed, and the measurement of diversity index is further improved to make it more accurate. The improved algorithm is tested on six basic functions and CEC2017 test function to verify its effectiveness. Finally, the improved algorithm is applied to the three-dimensional path planning of UAV with threat area. The results show that the improved algorithm has stronger optimization performance, has strong competitiveness compared with other algorithms, and can quickly plan the effective and stable path of UAV, which improves an effective method for the application in this field and other fields.