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Use of Fuzzy Evidential Reasoning for Vessel Selection Under Uncertainty

In: Multi-Criteria Decision Making in Maritime Studies and Logistics

Author

Listed:
  • Zaili Yang

    (Liverpool John Moores University)

  • Lefteris Maistralis

    (ABS Maritime Services (Hellas) LLC)

  • Stephen Bonsall

    (Liverpool John Moores University)

  • Jin Wang

    (Liverpool John Moores University)

Abstract

The selection of appropriate vessels to carry out shipping activities is crucial for many maritime stakeholders including charterers, shipowners, brokers, surveyors and safety engineers. The task is essentially a process of multiple criterion decision making under uncertainty requiring analysts to derive rational decisions from uncertain and incomplete data contained in different quantitative and qualitative forms. The difficulty and complexity of such a task is obvious and thus stimulates the study of developing a novel decision making technique under uncertainty with multiple criteria. This chapter aims to use the new function of fuzzy Evidential Reasoning to improve the vessel selection process of dealing with multiple criteria with insufficient and ambiguous information. A numerical case study of selecting an oil tanker based on a voyage charter party is presented to demonstrate the proposed method.

Suggested Citation

  • Zaili Yang & Lefteris Maistralis & Stephen Bonsall & Jin Wang, 2018. "Use of Fuzzy Evidential Reasoning for Vessel Selection Under Uncertainty," International Series in Operations Research & Management Science, in: Paul Tae-Woo Lee & Zaili Yang (ed.), Multi-Criteria Decision Making in Maritime Studies and Logistics, chapter 0, pages 105-121, Springer.
  • Handle: RePEc:spr:isochp:978-3-319-62338-2_5
    DOI: 10.1007/978-3-319-62338-2_5
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    Cited by:

    1. Görçün, Ömer Faruk, 2022. "A novel integrated MCDM framework based on Type-2 neutrosophic fuzzy sets (T2NN) for the selection of proper Second-Hand chemical tankers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

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