Approximate TOPSIS for vessel selection under uncertain environment |
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| Authors: | ZL Yang S Bonsall J Wang |
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| Affiliation: | 1. Department of Maritime Management, Piri Reis University, Tuzla, 34940, Istanbul, Turkey;2. Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Tuzla, 34940, Istanbul, Turkey;1. University of Pretoria, 2 Lynnwood Rd, Pretoria, South Africa;2. Council for Scientific and Industrial Research, Meiring Naudé Rd, Lynnwood, Pretoria, South Africa;1. Tyndall Centre for Climate Change Research, School of Mechanical, Aerospace and Civil Engineering, University of Manchester, United Kingdom;2. Natural Resources Institute, Department of Agriculture Health and Environment, University of Greenwich, United Kingdom;3. Faculty of Science, Agriculture and Engineering (SAgE), Newcastle University, Newcastle upon Tyne, United Kingdom;1. Department of Electrical, Electronic and Computer Engineering, University of Pretoria, 2 Lynnwood Rd, Pretoria, South Africa;2. Council for Scientific and Industrial Research, Meiring Naudé Rd, Lynnwood, Pretoria, South Africa;1. Departamento de Máquinas y Motores Térmicos, Escuela de Ingenierías Marina, Náutica y Radioelectrónica, Campus de Excelencia Internacional del Mar (CEIMAR), Universidad de Cádiz, Spain;2. Hellenic Institute of Transport, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece;3. Departamento de Máquinas y Motores Térmicos, Universidad de La Coruña, Spain |
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| 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 criteria decision making (MCDM) under uncertainty requiring analysts to derive rational decisions from ambiguous and incomplete data contained in different quantitative and qualitative forms. Fuzzy Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) have been well documented in the literature and commonly used in the process of group decision-making under fuzzy environment. While showing the attractiveness in dealing with ambiguous estimates, they have been criticised to be incapable of modelling incompleteness encountered in decision analysis. This paper therefore uses the concept of degrees of belief to develop a novel approximate interval TOPSIS approach for overcoming some of the drawbacks of classical fuzzy TOPSIS methods and facilitating the development of reliable vessel selection models under uncertain environment. |
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