Neural networks based forecasting techniques for inventory control applications

An increasing number of organizations are involved in the development of information systems for effective linkages with their suppliers, customers, and other channel partners involved in transportation, distribution, warehousing and maintenance activities. We use neural network based data mining and knowledge discovery techniques to solve the problems of inventory in a large medical distribution company. The paper describes the use of traditional statistical techniques to evaluate the best neural network type. Based on the neural network model described in this paper, a prototype was conceived with data from a large decentralized organization. The prototype was successful in reducing the total level of inventory by 50% in the organization, while maintaining the same level of probability that a particular customer's demand will be satisfied.