A Bayesian Method for Decision of Weight for MADM Model with Interval Data

Abstract

The weight in TOPSIS approach (technique for order preference by similarity ideal solution -TOPSIS ) is given by experts or decision makers. The value of weight would be influenced by experts' subjective judgments. A slight difference in value of weight may result in diversity of order of alternatives. In this paper, a Bayesian method for decision of weight for MADM model with interval data is introduced. The value of weight is decided by prior information (other experts' knowledge, or numerical simulation etc.) and experts' knowledge (or decision makers' experience/ preference). This method effectively takes advantage of experts' knowledge and avoids the problem with experts' subjectivity. An illustrative example is showed to explore the applications of proposed method. The method is valuable for field of multi-attribute decisionmaking with interval data.

Achieving Consensus with Individual Centrality Approach

“…Hard consensus has an interval [0,1]. It has been employed in ([1]; [11]; [8]; [30]) and generally has several methods to calculate a consensus degree, i.e. : · Count number of experts.…”

“…The most popular is AHP and its variant to achieve consensus ( [17]; [4]; [28]; [9]; [19]; [16]; [12]). Other methods also have been commonly used such as: ELECTRE TRI ( [22]; [18]), TOPSIS [30], and MAUT [8]. 4.…”

On the Use of Hybrid Heuristics for Providing Service to Select the Return Channel in an Interactive Digital TV Environment

“…The European approach has a wider range of multicriteria decision methods, such as TOPSIS, elimination and choice translating reality (ELECTRE), measuring atractiveness by a categorical-based evaluation technique (MACBETH), among others [24].…”

“…[24], "the weight in technique for order preference by similarity ideal solution (TOPSIS) is given by experts or decision makers. The value of weight would be inluenced by expertspsila subjective judgments.…”