一种求解背包问题的新的神经网络模型

A New ANN of Solving Knap Problem

背包问题是一类经典的组合优化问题 ,在网络资源分配中有着广泛的运用。人工神经网络已成为求解大规模优化问题的一种有效方法 ,已经证明合适的神经网络能实时地得到问题的精确解。研究了背包问题的神经网络解法 ,给出了一种求解背包问题的新的神经网络模型 ,并证明了该网络模型收敛到背包问题的最优解。

The knap problem is a classical combinatorial optimization problem which plays an important role in a network source assignment. Artificial neural network (ANN) has been an effective method to solve the large-scale optimal problem. It's proved that the neural network can get the exact solutions to the problem if it is tuned appropriately. In this paper, the artificial neural network for the knap problem is explored. A new neural network to solve knap problem is presented. The proposed neural network is proved to be completely stable to the exact solutions. The simulation examples show its efficiency and the validity in finding the optimum solution to knap problem.