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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14562

Title: TOPSIS and its Extensions: Applications for Road Safety Performance Evaluation
Authors: Bao, Qiong
Ruan, Da
Shen, Yongjun
Hermans, Elke
Janssens, Davy
Issue Date: 2012
Publisher: Springer
Citation: Kahraman, Cengiz (Ed.). Computational Intelligence Systems in Industrial Engineering, p. 109-130
Series/Report: Atlantis Computational Intelligence Sytems
Series/Report no.: 6
Abstract: Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the well-known classical multi-criteria decision-making (MCDM) techniques. In this chapter we illustrate the use of this method to combine individual safety performance indicators (SPIs) into an overall index of road safety performance for a set of European countries. In this respect, to deal with the subjective kind of uncertainty on data (such as linguistic variables given by experts) which are usually adopted to assess the weights of criteria/indicators, we explore an extension of the classical TOPSIS method to fuzzy environments. Moreover, due to the ever increasing number of SPIs used to reflect each road safety risk factor in a more comprehensive way, we consider a hierarchical structure of the indicators in this study. Accordingly, a hierarchical fuzzy TOPSIS model is realized and applied to combine the multilayer indicators into one overall index. Comparison of the resuls based on the three models (i.e., the classical TOPSIS, the fuzzy TOPSIS, and the hierarchical fuzzy TOPSIS) demonstrates the effectiveness of applying the hierarchical fuzzy TOPSIS method to handle the problem of linguistic expression instead of crisp values given by experts, and to take the layered hierarchy of the indicators into account which is seldom considered in the current road safety index research.
URI: http://hdl.handle.net/1942/14562
ISBN: 978-94-91216-77-0
ISSN: 1875-7650
Category: B2
Type: Book Section
Validation: vabb, 2014
Appears in Collections: Research publications

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