An integrated methodology for supplier selection and order allocation in the presence of imprecise data

Abstract

There has been numerous number of studies related to the supplier selection and problems which adopted a variety of approaches to solve them, however, based on our knowledge none of them has been considered the major decisions related to supplier selection and order allocation in the presence of imprecise data. In an attempt to fulfil this gap, we present an integrated framework which involves two stages including supplier evaluation and order allocation. An augmented imprecise data envelopment analysis (AIDEA) is proposed for supplier evaluation as the basic IDEA model has two main drawbacks, i.e., unrealistic input-output weights and poor discriminating power among all suppliers. Then, an integer programming with fuzzy objectives and constraints is formulated to assign optimal quantity of order to allocated suppliers. The efficiency of suppliers derived from evaluation stage is an important link which integrates these two stages. Finally, the integrated methodology is implemented in a case study organisation.