A supplier selection and order allocation model with multiple transportation alternatives

Numerous analytical methods ranging from simple weighted scoring to complex mathematical programming approaches have been proposed to solve supplier selection and order allocation problems. However, the traditional methods too often fail to consider: (1) situations in which goods are transported from a supplier to a receiver using different transportation alternatives (TAs) and (2) a finite planning horizon consisting of multiple discrete time periods. We present a structured framework with two separate but dependent phases. In the selection phase, we use a data envelopment analysis model to determine the relative efficiency of the suppliers and the TAs. In the allocation phase, we use a multi-objective mixed integer programming model with two objectives for minimizing the total costs and maximizing the overall efficiencies. The contribution of this paper is threefold: (1) It provides a comprehensive and systematic framework that embraces both quantitative and qualitative criteria; (2) it addresses the need in the supplier evaluation literature for methods that considers different TAs in the supplier selection and order allocation decisions encompassing multiple discrete time periods; and (3) it uses a real-world case study to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.