Suppliers selection based on intuitionistic fuzzy dimensional analysis

Author:

Pérez-Domínguez Luis1,David Luviano-Cruz1,Picón Luis Alberto Rodríguez1,López Roberto Romero1,Yohana Sánchez-Mojica Karla2

Affiliation:

1. Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Ave. Del Charro 450 Norte, Ciudad Juarez, Chihuahua, Mexico

2. Departamento de Investigación, Fundación de Estudios Superiores Comfanorte FESC, Avenida 5 15-27, Centro, Cúcuta, Colombia

Abstract

Supplier selection is a crucial activity in the supply chain management, and fundamentally it is a multi-criteria decision-making problem. However, the interaction of the criteria, the uncertain regarding to subjectivity and the imprecise information generally present in the provider selection process is still an open issue. The main purpose of this paper is to arise a new method to support the provider selection process. In this sense, this paper introduces the intuitionistic fuzzy version of dimensional analysis under a group decision making and multi-criteria environment applied to suppliers selection. Likewise, a set of decision makers reveal their preferences about the criteria and options in evaluation by mean of a linguistic grade that are mapped via intuitionistic numbers. Consequently, the importance of each decision maker and criteria is considered in the method. Hence, the methodology assumes that exist a choice better than the rest which is called ideal alternative. Each choice in evaluation, is compared with that ideal to induce an index of similarity. Additionally, the alternative with highest index of similarity is proposed as solution to the supplier selection problem. The method offer a systematic mode to deal with the interrelationship between the criteria attached into the decision making sphere. Finally, a numerical example is addressed to supplier selection to facilitate the understanding of the proposed method.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference78 articles.

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