关键词: 粒子群优化, 神经网络, 0/1优化问题

Abstract: A hybrid PSO algorithm was proposed, where the Hopfield manpower neural network with better local searching ability was combined with PSO for solving a class of 0/1 knapsack problem. The current global optimum chromosome activated the neural network and obtained a local optimum state that was used to replace the current global optimum chromosome in this algorithm. Local optimization ability of the algorithm was strengthened. Numerical test shows that this algorithm is effective.

Key words: Particle Swarm Optimization (PSO), neural network, 0/1 optimization problem