A novel artificial fish swarm algorithm for solving large-scale reliability–redundancy application problem. (November 2015) - He, Qiang; Hu, Xiangtao; Ren, Hong; Zhang, Hongqi
Abstract: A novel artificial fish swarm algorithm (NAFSA) is proposed for solving large-scale reliability-redundancy allocation problem (RAP). In NAFSA, the social behaviors of fish swarm are classified in three ways: foraging behavior, reproductive behavior, and random behavior. The foraging behavior designs two position-updating strategies. And, the selection and crossover operators are applied to define the reproductive ability of an artificial fish. For the random behavior, which is essentially a mutation strategy, the basic cloud generator is used as the mutation operator. Finally, numerical results of four benchmark problems and a large-scale RAP are reported and compared. NAFSA shows good performance in terms of computational accuracy and computational efficiency for large scale RAP. Highlights: We design three kinds of artificial fish behaviors. We apply two position-updating strategies to define the foraging behavior. We apply the selection and crossover operators to define the reproductive behavior. We apply cloud model to define the random behavior.