Multi-criteria Based Selection of Ship-Based Ballast Water Treatment Technologies

Eugene Pam, Alan Wall, Zaili Yang, Eddie Blanco-Davis and Jin Wang ()
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Eugene Pam: Liverpool John Moores University
Alan Wall: Liverpool John Moores University
Zaili Yang: Liverpool John Moores University
Eddie Blanco-Davis: Liverpool John Moores University
Jin Wang: Liverpool John Moores University

A chapter in Advances in Reliability and Maintainability Methods and Engineering Applications, 2023, pp 3-19 from Springer

Abstract: Abstract The reality of selecting an acceptable ballast water treatment technology is a daunting task for end-users, due to availability of numerous treatment options and their efficacy in given ship-types and ballast voyages. Six treatment systems have been selected from the two generic treatment technology groups (physical solid liquid separation and disinfection), and are considered as the decision-making alternatives in the proposed model. The proposed model involves the application of the Technique for Order Performance by Similarity to the Ideal Solution (TOPSIS), in the decision-making analysis. The TOPSIS technique has been applied to obtain the performance ratings of the decision alternatives using linguistic terms parameterised with triangular fuzzy numbers. A sensitivity study is also conducted to identify the effects of changes in input data, and test the suitability of the developed model in decision-making analysis of ballast water treatment systems.

Keywords: Multiple criteria; Ballast water; TOPSIS; Decision making (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-031-28859-3_1

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DOI: 10.1007/978-3-031-28859-3_1

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