Neural network fundamentals with graphs, algorithms, and applications
Neural network fundamentals with graphs, algorithms, and applications
An integrated model for supplier selection decisions in configuration changes
Expert Systems with Applications: An International Journal
Sourcing with random yields and stochastic demand: A newsvendor approach
Computers and Operations Research
An integrated multicriteria decision-making methodology for outsourcing management
Computers and Operations Research
A hybrid approach to supplier selection for the maintenance of a competitive supply chain
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A Fuzzy agent-based model for reduction of bullwhip effect in supply chain systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Supplier selection based on hierarchical potential support vector machine
Expert Systems with Applications: An International Journal
Analytic network process and multi-period goal programming integration in purchasing decisions
Computers and Industrial Engineering
Supplier selection: A hybrid model using DEA, decision tree and neural network
Expert Systems with Applications: An International Journal
An effective supplier selection method for constructing a competitive supply-relationship
Expert Systems with Applications: An International Journal
Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management
Fuzzy Optimization and Decision Making
Supplier selection using AHP methodology extended by D numbers
Expert Systems with Applications: An International Journal
A mixed-integer non-linear program to model dynamic supplier selection problem
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
The purpose of this paper is to aid just-in-time (JIT) manufacturers in selecting the most appropriate suppliers and in evaluating supplier performance. Many manufacturers employ the JIT philosophy in order to be more competitive in today's global market. The success of JIT on the production floor has led many firms to expand the JIT philosophy to the entire supply chain. The procurement of parts and materials is a very important issue in the successful and effective implementation of JIT; thus, supplier selection and performance evaluation in long-term relationships have became more critical in JIT production environments. The proposed systems can assist manufacturers in handling these issues. In this research, neural network based supplier selection and supplier performance evaluation systems are presented. The proposed approach is not limited to JIT supply. It can assist manufacturers in selecting the most appropriate suppliers and in evaluating supplier performance. The proposed neural network based systems are tested with data taken from an automotive factory, and the results show that the proposed systems can be used effectively.