A Multi-Criteria Interval Optimization Model for Manufacturing Supplier Selection Using Genetic Algorithm

This paper presents a multi-criteria interval optimization model to determine the optimal criteria values and then rank the candidate suppliers. Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclidean distance and vector theories. It is proved that the optimization objective function must have an optimal solution and genetic algorithm based on integer encoding is applied to obtain it. The computational results of a practical example suggested the proposed model and approach is satisfactory and the final choice is obtained. Finally, encouraging conclusions are given.