【摘要】 将局部寻优能力极强的人工Hopfield神经网络算法融合到粒子群优化算法的搜索过程中,提出解决一类0/1优化问题融合神经网络的混合粒子群优化算法。在该算法中依粒子群当前全局最优个体为初始态激活神经网络,生成一个局部最优态,用这个局部最优态代替粒子群当前全局最优个体,增强了算法的局部寻优能力,通过数值试验证明该算法是有效的。更多还原

【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.更多还原