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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/5017

Title: Assessment Aggregation in the Evidential Reasoning Approach to MADM Under Uncertainty : Orthogonal Versus Weighted Sum
Authors: Huynh, Van-Nam
Nakamori, Yoshiteru
Ho, Tu-Bao
Issue Date: 2005
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 3321
Start page: 109
End page: 127
Abstract: In this paper, we revisit the evidential reasoning (ER) approach to multiple-attribute decision making (MADM) with uncertainty. The attribute aggregation problem in MADM under uncertainty is generally formulated as a problem of evidence combination. Then several new aggregation schemes are proposed and simultaneously their theoretical features are explored. A numerical example traditionally examined in published sources on the ER approach is used to illustrate the proposed techniques.
Rights: This is the author-created version of Springer, Van-Nam Huynh, Yoshiteru Nakamori and Tu-Bao Ho, Lecture Notes in Computer Science, 3321, 2005, 109-127. The original publication is available at www.springerlink.com,
URI: http://hdl.handle.net/10119/5017
Material Type: author
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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