A multiagent artificial fish swarm algorithm
Lianguo Wang, Yi Hong · 2008
The efforts of this paper are proposed a multiagent artificial fish swarm algorithm(MAAFSA) by introducing the multiagent system to the artificial fish swarm algorithm(AFSA). This algorithm fixes the agent on grid, with the competition and cooperation with its neighbors, and combining the evolution mechanism of the AFSA algorithm, each agent unceasingly senses local environment, and gradually affects the whole agent grid, so that it enhances its adaptiveness to the environment. The agent shall also make self-study by using its knowledge to enhance its adaptiveness to the environment. This algorithm can effectively maintain the diversity of the population, and increase the precision of optimization, and simultaneously, efficiently restrain the prematurity. By the testing of high dimension benchmark functions and comparing with some optimization results of other methods, the results illustrate this algorithm has higher optimization performance in the field of high dimension functions optimization.