Application Of Neural Network In Planning Problem Of FMS

The application of neural network needs a set of prior system simulations as training illustrations to find out what the excellent rule is for all possible systems state. The machine learning algorithm Inductive Learning coupled along with neural network for the problem on hand is trained to attain knowledge via these training illustrations, and this knowledge is then utilized to build intelligent decisions in real time frame. These training illustrations can be produced by explaining a set of control attributes such are utilized to identify the state of manufacturing systems at all exacting time. Machine Learning, an idea based upon Artificial Intelligence, resolves the problem via the knowledge this had gained in the past throughout resolving the problem of same nature.

For resolving the machine loading problem in flexible manufacturing systems, Hopfield neural networks are utilized. Hopfield networks are extremely popular for resolving difficult combinatorial optimization problems like problem of job shop scheduling and common assignment. Conversely, the generation of feasible solutions is not easy through the employ of such networks, many researchers have employ its variations as like stochastic and deterministic Hopfield networks for resolving complex optimization problems.