Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
497146 | Applied Soft Computing | 2008 | 7 Pages |
Abstract
In supply chain management (SCM), multi-product and multi-period models are usually used to select the suppliers. In the real world of SCM, however, there are normally several echelons which need to be integrated into inventory management. This paper presents a hybrid intelligent algorithm, based on the push SCM, which uses a fuzzy neural network and a genetic algorithm to forecast the rate of demand, determine the material planning and select the optimal supplier. We test the proposed algorithm in a case study conducted in Iran.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Mohammad Reza Sadeghi Moghadam, Amir Afsar, Babak Sohrabi,