Evacuation Entropy Path Planning Model Based on Hybrid Ant Colony-Artificial Fish Swarm Algorithms

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Wang, Fang^1 ; Wang, Jian^1 ; Chen, Xiaowei^1

CIMS Research Center, Tongji University, Shanghai, China^1

关键词: Ant colony algorithms;    Artificial fish swarm algorithms;    Convergence speed;    Crowding factors;    Fast convergence speed;    Feedback mechanisms;    Initial solution;    Optimal solutions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/5/052025/pdf
DOI  :  10.1088/1757-899X/563/5/052025

来源: IOP

【 摘 要 】

The artificial fish swarm algorithm is introduced to construct the evacuation entropy path planning model of hybrid ant colony-artificial fish swarm algorithm to improve the convergence speed of the model. In the early stage of the model, the advantage of artificial fish swarm algorithm is used to search the optimal solution quickly and generate the initial solution. In the later stage of the model, the strong positive feedback mechanism of ant colony algorithm is used to quickly iterate out the optimal path. At the same time, the crowding factor of artificial fish swarm algorithm is introduced to update local pheromones adaptively combined with evacuation entropy. The simulation results show that the hybrid ant colony-artificial fish swarm algorithm has fast convergence speed and can avoid falling into local optimum.