An Integrated MCDM Approach to Train Derailment Risk Response Strategy Selection

Autor: Huafeng Zhang, Quanxin Sun
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Symmetry, Vol 12, Iss 1, p 47 (2019)
Druh dokumentu: article
ISSN: 2073-8994
DOI: 10.3390/sym12010047
Popis: Train derailment can mainly cause not only economic losses in the shape of mangled rolling stock or infrastructure, but also more severely in causalities and disruptions of operations, yielding great impact on the sustainable development of railway industry. Considering various complex and symmetrical operational environments, as well as the characteristics of low frequency and high consequences of derailment accidents, risk response is undoubtedly underlined as one of the most critical components of risk management process. However, in practice, risk response does not receive enough attention in comparison with risk assessment that it lacks mature models and tools for selecting optimal strategy. This study constructs an integrated Multi Criteria Decision-Making (MCDM) model for the selection of optimum train derailment risk response strategy for the first time. In the model, decision making trial and evaluation laboratory (DEMATEL) technology is connected with analytical network process (ANP) to obtain evaluation criteria and their relative weights, and both of the two methods can deal with the complex coupling relationship between the indicators in the system. Then, technique for order performance by similarity to ideal solution (TOPSIS) is proposed to screen the optimum plan in the proposed model. Further, the Delphi method is used through the whole process to acquire expert advice. In the end, this model is used to select shunting derailment risk response strategies in Huangyangcheng station, and the final results demonstrate that this technology is simple and practical, and can provide a credible and practical tool for railway safety managers and engineers to choose the best risk response strategy.
Databáze: Directory of Open Access Journals
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