Application of an annealed neural network to a timetabling problem

In this paper, we use an annealed neural network to solve a timetabling problem with contiguity and availability constraints. A novel feature of the problem is that it may not be possible to satisfy the complete set of scheduling requirements, forcing the network to exhibit selection capability. We formulate the problem in a manner consistent with neural computation, describe our implementation of the annealed neural network, and report computational results for a series of randomly-generated problems. Solution quality varies depending on the size and difficulty of the problem, as well as on the values of the penalty parameters used to weight the various constraints.