Title :
An Improved Artificial Fish Swarm Algorithm for Resource Leveling
Author :
Tian, WenJie ; Tian, Yue
Author_Institution :
Autom. Inst., Beijing Union Univ., Beijing, China
Abstract :
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.
Keywords :
convergence; optimisation; resource allocation; artificial fish swarm algorithm; global convergence; local optimization; resource leveling; Ant colony optimization; Automation; Convergence; Finance; Forward contracts; Marine animals; Particle swarm optimization; Robustness; Signal processing algorithms; Uncertainty;
Conference_Titel :
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4638-4
Electronic_ISBN :
978-1-4244-4639-1
DOI :
10.1109/ICMSS.2009.5302122