A fuzzy MCDM model for allocating orders to suppliers in a supply chain under uncertainty over a multi-period time horizon

Allocating orders to suppliers is of a great importance in managing the supply chain. This process comes after supplier selection and evaluation. Having selected the qualified vendors, the manager will examine the performance of each one and evaluate the individual vendor. According to the results of periodic evaluations, the manager allocates orders to suppliers. Splitting orders among suppliers is so important that it may influence the efficiency of the whole chain. In this paper, we propose a fuzzy multi-criterion model for organizing the process of assigning orders to suppliers. We adopt a fuzzy approach in order to overcome the vagueness of the information due to the uncertainty of them. MCDM methods are used to allocate suitable shares of orders to the best possible suppliers. Different from previous works, we discuss this problem over a multi-period time horizon; namely, the model leads to solutions which optimize the order in both the whole year and the fractional periods of a year. A fuzzy linear programming model is developed to optimize the price, quality and risk objectives and satisfy constraints like logistics costs, suppliers′ capacity, supply chain demand, risk, etc. A numerical example comes to validate our proposed model.

Research highlights
► We propose a fuzzy MCDM model to allocate orders to suppliers in a supply chain.
► We consider the model under uncertainty, so fuzzy approach is adopted.
► Different conditions of multi-period time horizon are considered.
► Our proposed model optimizes cost, quality and risk.
► A numerical example validates the model.