Optimization of Supply Chain Link Using Neural Network

In today’s world of competitive business, coordination of business activities is very important in order to survive in the market. SCM is a concept that assumes a business as a chain of inter-connected entities of commercial activities. The coordination of data and material transfer should be fast and controlled to achieve better performance, so to coordinate all these activities an efficient algorithm is required to optimize the Supply chain link hierarchy.

          This project discusses the application of Neural Network to propose a co-operation model for SCM. This model constructs a relevant Supply Chain through iterated Match-Making process. The Match Making process makes connection between service provider and service requestor for each link of the supply chain. Effective supply chain is made when each link in the Supply Chain is connected properly. The proposed model uses Neural Network to establish proper connection between each link.

          The developed Neural Network model predicts the optimal solution for any set of problem instances. Back propagation approach is used for training the Neural Network. Feed Forward Back Propagation approach is found to be effective in finding optimum chain connection from the procurement to the customer. Decisions are made based on the optimum solution obtained using neural network approach for selecting suppliers.


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