关键词: 优化问题, 人工鱼群算法, 云模型, 进化算法

Abstract: In this paper, the social behaviors of fish swarm are classified in three ways： foraging behavior, reproductive behavior, and flight behavior. Inspired by this, a Novel Artificial Fish Swarm Algorithm（NAFSA） is proposed, which integrates the mutation strategy and evolution behavior into the social behaviors of fish swarm. In the case of mutation strategy, the basic cloud generator is used as the mutation operator because of the properties of randomness and stable tendency of a normal cloud model. For the reproductive behavior, the selection, and crossover operator in evolutionary algorithm are applied to define the reproductive ability of an artificial fish. Furthermore, the parameters of step and visual are developed in forms of hyperbolic tangent function to adjust the optimize performance dynamically during iterations process. Ten standard test functions are used as the benchmark to validate the effectiveness of the NAFSA. Experimental results have confirmed the superiority of NAFSA in terms of both solution quality and convergence speed, and shown broad application prospect in engineering.

Key words: optimization problem, artificial fish-swarm algorithm, cloud model, evolutionary algorithm