Artificial neural networks (ANNs) attempt to emulate the massively parallel and distributed processing of the human brain. They are being examined for a variety of problems that have been difficult to solve with current serial type computing and processing; incuding a wide variety of combinatorial optimization problems. This paper deals with scheduling problems involving ANN applications. The objective is to review the entire literature of neural networks that are applied to various scheduling problems ranging from a single machine scheduling to satellite broadcasting scheduling. Both the theoretical developments and computational experiences are discussed. A classification framework is provided. Future research directions are also suggested.