Multi objective and multi echelon solution approaches for supply chain network design problem

In this thesis, a multi criteria decision making approach, a multi objective mathematical model and a metaheuristic approach are developed for supplier selection and supply chain network design problems. The supply chain network of a production company is considered in order to show the efficiency of proposed approaches. Since the location of the production plant is fixed the supply chain network design problem divided into two separate problem. The first problem focuses on creating the network between the suppliers and production plant while the second problem focuses on creating the network between production plant, warehouses and customers. The first problem is thought as a supplier selection problem. Therefore, first the criteria and criteria weights which affect the supplier selection are determined and then the suppliers are evaluated according to those criteria. Since, there are both qualitative and quantitative criteria, it became necessary to use an algorithm which gives the opportunity of analyzing both qualitative and quantitative criteria together. For this reason, Buckley's Fuzzy AHP Algorithm is used for the first problem. For the second problem, a multi objective mathematical model is created and it is solved according to the data obtained from the company. The computational results showed that the model gives optimum solution within reasonable time. However, since the problem is an NP-Hard class problem, this model cannot find the optimum solution in big dimensional problems. For this reason, a metaheuristic approach is developed. The computational results of the metaheuristic approach shows that the proposed approach gives high quality solutions within less than a second.