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Ship selection using a multiple-criteria synthesis approach

Xie, Xinlian; Xu, Dong-Ling; Yang, Jian-Bo; Wang, Jin; Ren, Jun; Yu, Shijun

Journal of Marine Science and Technology. 2008;13(1):50-62.

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Abstract

Abstract A method is presented for selecting a preferred ship from a group of candidates as a reference ship for a new design. The method is based on a recently developed approach for multiple-criteria decision analysis under uncertainty, the evidential reasoning approach. Using this method, both quantitative and qualitative attributes of a complicated nature can be considered in the selection process. The method consists of three phases: identifying suitable candidate ships, evaluating them in terms of both conventional techno-economical and qualitative attributes, and aggregating all the attributes using the evidential reasoning approach. This three-phase procedure is illustrated by means of an oil tanker selection example. The results of this study show that the evidential reasoning approach can support multiple-criteria ship selection processes when both qualitative and quantitative information with or without uncertainties have to be taken into account. The outcomes generated by the method include the ranking of the candidate ships and indications of their strengths and weaknesses in the format of performance distributions over different assessment grades. Such information is vital in helping decision makers to make an informed selection and be aware of any risk implication associated with the selection.

Bibliographic metadata

Type of resource:
Content type:
Publication type:
Publication form:
Published date:
Publishers website:
http://dx.doi.org/10.1007/s00773-007-0259-4
Volume:
13
Issue:
1
Start page:
50
End page:
62
Total:
13
Pagination:
50-62
Digital Object Identifier:
10.1007/s00773-007-0259-4
Access state:
Active

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:1g131
Created:
21st September, 2009, 22:21:18
Last modified:
28th May, 2015, 19:47:22

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