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John, A, Paraskevadakis, D, Bury, A, Yang, Z, Riahi, R and Wang, J (2014) An integrated fuzzy risk assessment for seaport operations. SAFETY SCIENCE, 68. pp. 180-194. ISSN 0925-7535
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Abstract
Seaport operations are characterised by high levels of uncertainty, as a result their risk evaluation is a very challenging task. Much of the available data associated with the system’s operations is uncertain and ambiguous, requiring a flexible yet robust approach of handling both quantitative and qualitative data as well as a means of updating existing information as new data becomes available. Conventional risk modelling approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the system’s risks. This paper proposes a novel fuzzy risk assessment approach to facilitating the treatment of uncertainties in seaport operations and to optimise its performance effectiveness in a systematic manner. The methodology consists of a fuzzy analytical hierarchy process, an evidential reasoning (ER) approach, fuzzy set theory and expected utility. The fuzzy analytical hierarchy process is used to analyse the complex structure of seaport operations and determine the weights of risk factors while ER is used to synthesise them. The methodology provides a robust mathematical framework for collaborative modelling of the system and allows for a step by step analysis of the system in a systematic manner. It is envisaged that the proposed approach could provide managers and infrastructure analysts with a flexible tool to enhance the resilience of the system in a systematic manner.
| Item Type: | Article |
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| Uncontrolled Keywords: | 09 Engineering, 11 Medical And Health Sciences, 17 Psychology And Cognitive Sciences |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management H Social Sciences > HE Transportation and Communications |
| Divisions: | Education |
| Publisher: | ELSEVIER SCIENCE BV |
| Related URLs: | |
| Date Deposited: | 14 Mar 2018 16:35 |
| Last Modified: | 04 Sep 2021 14:06 |
| DOI or ID number: | 10.1016/j.ssci.2014.04.001 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/1787 |
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