USING HOPFIELD TO SOLVE RESOURCE-LEVELING PROBLEM

The resource leveling problem in Network planning is a combinatorial NP problem. In this paper, in order to give the neural network description of resource leveling problem, the new concept of Augmented Permute Matrix (AMP) is proposed. Some novel technologies are using when setting up the energy function under time and resources constrains. An Embedded Hybrid Model combining Discrete-time Hopfield model and SA (DHNN-SA) is put forward to improve the optimization in essence in which Hopfield servers as State Generator for the SA. The comparison with professional project management software shows that the energy function and hybrid model given in this paper is highly efficient in solving resource leveling problem to some extent.