Abstract:

Since artificial fish swarm algorithm (AFSA) is easy to fall into local optimum at the latter stage, the accuracy and convergence rate of optimization are reduced. Aiming at this problem, we propose an improved algorithm, called DNAAFSA, which applies the crossover and mutation operations of the DNA algorithm to the basic AFSA. The proposed algorithm can enrich the diversity of fish stocks, thus helping the artificial fish escape from local optima. The DNAAFSA is applied to solve the location allocation problem of distribution centers and the simulation results show that the DNAAFSA has better optimization capability.

Key words: location allocation of distribution centers;DNAFASA;crossover of DNA;mutation of DNA