Evaluation and Selection of a Supplier by Interval DEA Models with Assurance Region: ADEA Approach to Efficient and Inefficient Frontiers

Subject Areas : Industrial Management

Hossein Azizi ¹ , Akbar Jafari Shaerlar ²

1 - Department of Applied Mathematics, Parsabad Moghan Branch, Islamic Azad University, Parsabad Moghan, Iran
2 - Department of Applied mathematics, Parsabad Moghan Branch, Islamic Azad University, Parsabad Moghan, Iran

Received: 2018-01-07 Accepted : 2018-01-07 Published : 2013-11-22

Keywords:

Abstract :

Traditionally, suppliers evaluation and selection models based on basic data put less emphasis on ordinal data; however, with the extensive use of production philosophies, such as Just In Time (JIT) production, further emphasis is put on considering cardinal and ordinal data simultaneously through the supplier selection process. Application of Data Envelopment Analysis (DEA) for the issues concerning the evaluation and selection of the supplier is based on the complete flexibility of weights. Yet, the problem is permissibility of complete flexibility of their weights, as the weight values obtained through the solving unrestricted DEA program are often contrary to the earlier viewpoints or the additional information. The present paper aims to propose interval DEA models with assurance region for evaluation and selection of the best supplier in the presence of weight restrictions and imprecise data. It proposes a new approach based on “DEA with efficient and inefficient frontiers” for evaluation and selection of the best supplier in the presence of weight restrictions and imprecise data. In this approach, optimistic and pessimistic efficiencies are considered simultaneously for each supplier. When the assurance region constraints are added to the interval DEA optimistic models, scores of calculated efficiency interval become worse and a supplier previously determined as the optimistic efficient supplier may be recognized as optimistic non-efficient. When the assurance region constraints are added to the interval DEA pessimistic models, scores of calculated efficiency interval are improved and a supplier previously recognized as a pessimistic inefficient supplier may be recognized as pessimistic non-inefficient. Comparing traditional DEA, DEA approach with efficient and inefficient frontiers may recognize the best supplier correctly and conveniently. A numerical example shows the application of the proposed approach.  

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