Artificial Fish Swarm Algorithm And Its Application

As a new type of random search algorithms, intelligent optimization ones generally refer to those gradually developed based on the similarity of natural biological systems with the optimization Process. They get next generation of solutions through operating on a set of solutions in the search space according to statistical rules.Artificial Fish Swarm Algorithm (AFSA) is such a new intelligent optimization ones, an evolutionary computation technique based on intelligence bionic optimization algorithm. The AFSA has a stronger robustness; the fine distributed computing and easy to union with other methods. At present, this algorithm research has already improved many other applications and has developed from a one-dimensional static state optimization solution to a multi-dimensional dynamic combination optimization solution.The main works of this paper are as follows:(1) Adopt the AFSA to adjust and optimize the path planning of robot。A calculation for an example has been done and the computation result shows that this method has some advantages as convergence and computation precision。(2) A new method is presented to calculate numerical integration based on artificial fish-swarm algorithm. The method which is based on inequality point's segmentation for solving numerical integration can not only compute usual definite integral for any functions, but also compute singular integral and oscillatory integral.(3) A new method is presented to calculate two-dimensional numerical integration based on artificial fish-swarm algorithm. The method is based on inequality point's segmentation for solving numerical integration. A parameter is been introduced into expression of integral sum. Finally, several experimental results show that our proposed numerical integration method is more efficient and feasible compared with other numerical integration methods.