Research Application Based On Multi-agent And Fish Swarm Algorithm

The Artificial Fish Swarm Algorithm is a new stochastic optimization algorithm based on group intelligent, essentially is a complex intelligent system. It has a stronger robustness; the fine distributed computing machine-made, easy to union with other methods, and so on. At present to this algorithm research, the application already seeped too many applications domain, and developed from the solution in unidimensional static state optimization questions to the solution in multi-dimensional dynamic combination optimization questions. The Artificial Fish Swarm Algorithm has already become in the interdisciplinary studies as an extremely active front research question.First, this paper briefly discusses the basic idea of AFSA, characteristics and the research present situation; elaborate to it conducts the improvement research significance. Then discussed several kinds method of multi-agent and Fish-swarm Algorithm and its fact application , which includes: multi-agent and fish-swarm algorithm used in the optimization of combination problems and its astringency is proved in this paper,constrained optimization based on adapting and chaos multi-agent and fish-swarm algorithm, optimization of multilevel hierarchical transshipment system in logistics transportation based on multi-agent and fish-swarm algorithm and optimization of location of speed fan in coal mine's ventilation system based on multi-agent and fish-swarm algorithm.The present paper has conducted the thorough research and the attempt to the Artificial Fish Swarm Algorithm improvement method, after the improvement, AFSA has the higher search efficiency and the gain optimal solution ability. The present paper research results have the important reference significance regarding the application of AFSA to solution actual optimization question. Further the thorough research also has the higher reference value to the next research on AFSA.