Artificial fish-swarm algorithm based on Von Neuman neighborhood
基于冯 诺依曼邻域结构的人工鱼群算法

An improved artificial fish-swarm algorithm based on Von Neuman neighborhood is proposed. In the algorithm each artificial fish is assumed to exchange messages only with neighboring artificial fish. This assumption reduces the computation time in finding the center and the extremum location within the neighborhood, while effectively retains the variety of the fish-swarm and increases the running speed of the algorithm. In the behavior of preying, the artificial fish will move directly to the superior position, raising the speed of searching. In the behavior of random swimming, the artificial fish will search the object in a region of small radius, improving the accuracy of searching. By dynamically adjusting the visual field and the step of searching for artificial fish, a compromise can be made between the ability of global search and the ability of local search. The experimental results show that the proposed algorithm has better optimization performance.