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On a Fuzzy AHP Weight for Partial Inner Dependence Structure

Authors:
Shin-ichi Ohnishi
Takahiro Yamanoi

Keywords: AHP; fuzzy set; sensitivity analysis

Abstract:
In a field of decision making for systems that contains human beings, the Analytic Hierarchy Process (AHP) is widely employed. It elicits weights of criteria and alternatives that are enough independent each other. For cases in which criteria are not enough independent, an extended inner dependence AHP is useful. In this paper, we investigate “partial inner dependence” structure, i.e., only some elements (proper subset) of the criteria are independent. For the partial inner dependence AHP, we propose a new kind of fuzzy weight representation that is valid even if a data matrix is not consistent or reliable enough. The new representation can be defined by using the results of two kinds of the sensitivity analyses. We finally show a numerical example of the fuzzy weight for partial inner dependence AHP.

Pages: 46 to 49

Copyright: Copyright (c) IARIA, 2017

Publication date: October 8, 2017

Published in: conference

ISSN: 2326-9286

ISBN: 978-1-61208-596-8

Location: Athens, Greece

Dates: from October 8, 2017 to October 12, 2017