Soft Computing

, Volume 23, Issue 24, pp 13215–13233 | Cite as

A decision support system for single-period single sourcing problem in supply chain management

  • Alireza EydiEmail author
  • Leyla Fazli
Methodologies and Application


A basic part of the logistic management of organizations is purchasing function, and appropriate supplier selection is one of the main responsibilities of this function. Appropriate supplier selection has an important role in reducing costs, increasing competitiveness and the share of market as well as improving customers’ satisfaction. Hence, the use of accurate and efficient techniques for supplier selection problems is out of question. Due to the importance of appropriate supplier selection, lots of research have been focused on this topic, but only a few of them considered the supplier selection problem with the process of reducing the set of all suppliers to a smaller set of eligible suppliers. Therefore, in this paper, based on data envelopment analysis models, a new hybrid methodology is presented for evaluating potential suppliers and selecting the best supplier (single sourcing) under certainty environment for a single-period by applying the strategy of reducing the number of potential suppliers. This methodology includes two phases: (1) classifying suppliers into efficient and inefficient suppliers, and hence reducing the set of all suppliers into a smaller set of eligible suppliers, and (2) evaluating the efficient (eligible) suppliers. Finally, a sample problem is demonstrated to examine the proposed methodology in comparison with traditional methods.


Supplier selection Single sourcing Pre-qualification of potential suppliers Single-period Data envelopment analysis models 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animal

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of EngineeringUniversity of KurdistanSanandajIran
  2. 2.Department of Industrial EngineeringFerdowsi University of MashhadMashhadIran

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