Method for Multiple Attribute Decision Making in Uncertain Linguistic Setting and Its Application to Supplier Selection

The aim of this paper is to investigate the multiple attribute decision making problems to deal with the supplier selection in supply chain management with uncertain linguistic information, in which the information about attribute weights is incompletely known, and the attribute values take the form of uncertain linguistic variables. We developed a multiple attribute decision making method to select supplier by similarity to ideal supplier alternative in uncertain linguistic setting, by which the attribute weights can be determined. We utilize the uncertain linguistic weighted average (ULWA) operator to aggregate the uncertain linguistic variables corresponding to each alternative, and then rank the alternatives by means of the aggregated linguistic information. Finally, an example about supplier selection is shown to highlight the procedure of the proposed algorithm.