Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Issue 4 (March 2015)

• Record Type: Journal Article
• Authors: You, Xiao-Yue; You, Jian-Xin; Liu, Hu-Chen; Zhen, Lu
• Is Part Of: Expert systems with applications. Volume 42:Issue 4(2015)
• Page Start: 1906
• Page End: 1916
• Publication Date: 2015-03
• Subjects: Group decision making -- Supplier selection -- VIKOR method -- Interval 2-tuple; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.10.004
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Propose an extended VIKOR method for group multi-criteria supplier selection. Diversity and uncertainty of decision makers' assessments are modeled using interval 2-tuples. Multiple and conflicting criteria are considered and evaluated by extended VIKOR method. The new method is more suitable to handle the supplier selection problem under uncertain environment. Abstract: How to select the suitable suppliers in the supply chain is critical for an organization's success and has attracted much attention of both researchers and practitioners. Supplier selection can be regarded as a complex group multiple criteria decision making problem requiring consideration of a number of alternative suppliers and quantitative and qualitative criteria. Additionally, decision makers cannot easily express their judgments on the alternatives with exact numerical values in many practical situations, and there usually exists uncertain and incomplete assessments. In response, this paper proposes an extended VIKOR method for group multi-criteria supplier selection with interval 2-tuple linguistic information. The feasibility and practicability of the proposed interval 2-tuple linguistic VIKOR (ITL-VIKOR) method are demonstrated through three realistic supplier selection examples and comparisons with the existing approaches. Results show that the ITL-VIKOR method being proposed is more suitable and effective to handle the supplier selection problem under vague, uncertain and incomplete information environment.