A Multi objective model for supplier evaluation and selection in the presence of both cardinal and imprecise data

  • Seyed Morteza Hatefi Faculty of Engineering, Shahrekord University, Rahbar Boulevard, PO Box 115, Shahrekord, Iran.
Keywords: IDEA, Multi-objective IDEA, Common weights, Discriminating power, Supplier selection

Abstract

Imprecise data envelopment analysis (IDEA) has been applied for supplier selection in the presence of both cardinal and imprecise data. In addition to its popularity, IDEA has some drawbacks such as unrealistic inputs-outputs weights and poor discrimination power among all DMUs. To alleviate these deficiencies, this paper develops a multi objective imprecise data envelopment analysis (MOIDEA) based on the common weights. The proposed MOIDEA model is utilized for supplier evaluation and selection in the case where there exist both cardinal and imprecise data. To show both robustness and discriminating power of the proposed approach, it is applied on a numerical example taken from the literature. The results reveal several merits of the common weight MOIDEA model for supplier selection.
Published
2017-04-06
How to Cite
Hatefi, S. M. (2017). A Multi objective model for supplier evaluation and selection in the presence of both cardinal and imprecise data. International Journal of Integrated Engineering, 9(2). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/1425
Section
Articles