Abstract:

As a swarm intelligence, the Artificial Fish Swarm Algorithm(AFSA) has its weakness in solving the problem of Multi-objective Knapsack, such as blindness search, low speed of convergence and low accuracy in solution. Combining the global information of the artificial fish position with improving the moving strategy of artificial fish self-adapting, an improved AFSA is proposed. Simulation on multi-objective knapsack problem shows that the convergence rate as well as the accuracy in the non-dominated solutions which have been found out in the improved AFSA is superior to Genetic Algorithm and Particle Swarm Optimization.

Key words: multi-objective optimization; Knapsack problem; artificial fish swarm algorithm; self-adaptive