Simulation study of an artificial fish swarm algorithm and application to UAV path planning

• Main Author: Wang, Xuyang
• Other Authors: Hu Guoqiang
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; Engineering; Multi-agent system; Artificial fish swarm algorithm; Path planning
• Online Access: https://hdl.handle.net/10356/174828
• Institution: Nanyang Technological University

In recent years, with the rapid change of science and technology, complex optimization problems are more and more common in many fields. These problems are very tricky in high-dimensional, nonlinear and multi-constraint scenarios, and traditional optimization methods are often difficult to deal with them efficiently and achieve the expected optimization results. How to solve complex optimization problems efficiently, quickly and accurately and apply them to the real world has become a big challenge. Faced with this challenge, Artificial Fish Swarm Algorithm (AFSA) shows its unique advantages in solving complex optimization problems with its unique swarm intelligence search mechanism. This dissertation is aimed at investigating the impact of the key parameters in the AFSA theoretical model on solving complex optimization problems. The purpose is to set the model parameters reasonably to maximize the performance of the algorithm. It is also applied to practical problem solving, especially the specific case of UAV path planning. Through simulation studies, the key parameters in the AFSA theoretical model are adjusted and optimized to achieve better simulation results. The reliable performance of AFSA in single UAV and multi-UAV path planning under 2D and 3D conditions is verified. Through the combination of theoretical model and practical application, this dissertation provides a new way for AFSA to solve complex problems in the real world and lays a solid foundation for future research in related fields.