A mathemathical model for supplier selection and order allocation in a supply chain considering uncertainty in design variables- for print

In most industries the cost of raw materials and component parts constitutes almost 60% percent of cost of a product (in some industries up to 80%). In this situation, proper sourcing can play a key role in an organization's efficiency and effectiveness, because it has a direct effect on cost reduction, profitability and flexibility of a company. In this paper, determining the optimal order quantity in multi supplier, multi product and during several periods, allowing shortage and surplus, in presence of incremental discounts, and considering multi objective and multi criteria nature of the problem, considering uncertainty in desing variables is considered. Demand of each product i in period t is assumed to be known. To incorporate the effective criteria in mathematical model, analytic network process approach is used. After developing the multi objective mixed integer programming, a numerical exampleis presented. In order to consider uncertainty in supplier evaluation and selection process, uncertainty is considered in design variables and the problem is solved by using genetic algorithm. In the mentioned model, problem is solved respect to robustness of design variables such that, a drastic change in these variables leads to the least possible effect on objective value. Ultimately fluctuations decrease as a result of uncertainty management. Finally results and suggestions for future studies are presented.