SWARM
An Improved Artificial Fish Swarm Algorithm for Multi Robot Task Scheduling
Wenjie Tian, Jicheng Liu
- 发表年份
- 2009
- 引用次数
- 11
摘要
The main aim of this study is managing robot tasks to minimize the deviation between the resource requirements and stated desirable levels. Some improved adaptive methods about step length are proposed in the artificial fish swarm algorithm (AFSA). In this study resource leveling methods are used to solve task scheduling problems in autonomous multi robot group. Robots are considered as resources. The experimental results show that proposed methods have better performances such as good and fast global convergence, strong robustness, insensitive to initial values, simplicity of implementation.
关键词
Swarm behaviourRobustness (evolution)RobotComputer scienceScheduling (production processes)Convergence (economics)Swarm roboticsAlgorithmArtificial intelligenceMathematical optimization
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 引用
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002