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G.R. Jahanshahloo, F.H. Lotfi and M. Izadikhah, “An Algorithmic Method to Extend TOPSIS for Decision-Making Problems with Interval Data”, Applied Mathematics and Computation, 175(2), 2006, pp. 1375-1384.

has been cited by the following article:

• TITLE: Extended TOPSISs for Belief Group Decision Making

  AUTHORS: Chao Fu

  KEYWORDS: basic belief assignment, belief group decision making, belief preferences aggregation, TOPSIS

  JOURNAL NAME: Journal of Service Science and Management, Vol.1 No.1, June 10, 2008

  ABSTRACT: Multiple attribute decision analysis (MADA) problems in the situation of belief group decision making (BGDM) are a special class of decision problems, where the attribute evaluations of each decision maker (DM) are represented by belief functions. In order to solve these special problems, in this paper, TOPSIS (technique for order preference by similarity to ideal solution) model is extended by three approaches, by which group preferences are aggregated in different manners. Corresponding to the three approaches, three extended TOPSIS models, the pre-model, post-model, and inter-model, are developed and their procedures are elaborated step by step. Aggregating group preferences in the three extended models respectively depends on Dempster’s rule or its modifications, some social choice functions, and some mean approaches. Furthermore, a numerical example clearly illustrates the procedures of the three extended models for BGDM.