Selecting scheduling heuristics using neural networks

This paper discusses the application of neural networks to select the best heuristic algorithm to solve a given scheduling problem. The two-stage hybrid flowshop with multiple identical parallel machines at the second stage is used as an example to discuss the process of selecting a scheduling heuristic through a neural-network approach. This paper uses the genetic-algorithm-based approach for training the neural network and shows that the suggested neural-network approach is quite effective and efficient for selecting the best heuristic algorithm for solving a given scheduling problem.