A two-level GA to solve an integrated multi-item supplier selection model

Official URL: http://dx.doi.org/10.1016/j.amc.2013.01.046

In this paper, we investigate an integrated multi-item supplier selection model. The mathematical model which is a nonlinear binary programming is derived. To the best of our knowledge, it is the first study in the literature that considers both integration and multi-item nature of supplier selection process. In addition, proposed model allows the buyer to select multiple suppliers. In the proposed model, inventory costs for both supplier/suppliers and buyer, production costs for supplier/suppliers, and transportation costs are considered where supplier/suppliers use EPQ model and the buyer uses EOQ model to control the inventories. To solve the proposed SCM model, based on genetic algorithm, a novel Two-Level heuristic algorithm is developed. The results show that the proposed algorithm works properly in the term of both CPU time and the quality of solutions. Finally, using numerical examples, some useful managerial analysis are presented. These analysis provide valuable insights into the problem that can help the supply chain managers.