Impulse artificial neural networks in internal transport

The second most important function of a warehouse, apart from the storing of goods, is internal transport with a focus on time-effectiveness. When there is a time gap between the production and export of products, the goods need to be stored until they are dispatched to the consumers. An important problem that concerns both large and small warehouses is the selection of priorities, that is handling the tasks in order of importance. Another problem is to identify the most efficient routes for forklift trucks to transport goods from a start-point to a desired destination and prevent the routes from overlapping. In automated warehouses, the transport of objects (the so called pallets of goods) is performed by machines controlled by a computer instead of a human operator. Thus, it is the computer, not the man, that makes the difficult decisions regarding parallel route planning, so that the materials are transported within the warehouse in near-optimal time. This paper presents a method for enhancing this process.