Economic Computation and Economic Cybernetics Studies and Research, Issue 1/2016, Vol. 50 _______________________________________________________________________________ 39 Mehdi KESHAVARZ GHORABAEE, PhD Candidate E-mail: m.keshavarz_gh@yahoo.com Department of Industrial Management, Faculty of Management and Accounting, AllamehTabataba’i University, Tehran, Iran ProfessorEdmundas Kazimieras ZAVADSKAS*, Dr.Sc. E-mail: edmundas.zavadskas@vgtu.lt (*corresponding author) Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Lithuania Professor Maghsoud AMIRI, PhD E-mail:amiri@atu.ac.ir Department of Industrial Management, Faculty of Management and Accounting,AllamehTabataba’i University, Tehran, Iran Professor Jurgita ANTUCHEVICIENE, PhD E-mail: jurgita.antucheviciene@vgtu.lt Department of Construction Technology and Management, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Lithuania A NEW METHOD OF ASSESSMENT BASED ON FUZZY RANKING AND AGGREGATED WEIGHTS (AFRAW) FOR MCDM PROBLEMS UNDER TYPE-2 FUZZY ENVIRONMENT Abstract. Fuzzy multi-criteria decision-making (MCDM) methods and problems have increasingly been considered in the past years. Type-1 fuzzy sets are usually used by decision-makers (DMs) to express their evaluations in the process of decision-making. Interval type-2 fuzzy sets (IT2FSs), which are extensions of type-1 fuzzy sets, have more degrees of flexibility in modeling of uncertainty. In this research, a new ranking method to calculate the ranking values of interval type-2 fuzzy sets is proposed. A comparison is performed to show the efficiency of this ranking method. Using the proposed ranking method and the arithmetic operations of IT2FSs, a new method of Assessment based on Fuzzy Ranking and Aggregated Weights (AFRAW)is developed for multi-criteria group decision-making. To obtain more realistic and practical weights for the criteria, the subjective weights expressed by DMs and objective weights calculated based on a deviation-based method are combined, and the aggregated weights are used in the proposed method. A numerical example related to assessment of suppliers in a supply chain and selecting the best one is used to illustrate the procedure of the proposed method. Moreover, a comparison and a sensitivity analysis are performed in this study. The results of these analyses show the validity and stability of the proposed method. Keywords: MCDM, interval type-2 fuzzy sets, fuzzy ranking method, multi-criteria group decision-making, AFRAW. JELClassification: C02, C44, C61, C63, L6