An Improved Artificial Fish Swarm Algorithm for Resource Leveling
Wenjie Tian, Yue Xia Tian · 2009
This paper provides an overview on the artificial fish swarm algorithm (AFSA) for the resource leveling. Some improved adaptive methods about step length are proposed in the AFSA. This method have better performances such as good and fast global convergence, strong robustness, insensitive to initial values, simplicity of implementation. The simulation results show that the resource leveling based on AFSA avoids premature effectively and prove its feasibility.