Author
Listed:
- Hakan Demirel
(Department of Marine Engineering, İstanbul Technical University, Istanbul 34940, Türkiye
Maritime Clean Energy Research Laboratory (MarCERLab), İstanbul Technical University, Istanbul 34940, Türkiye)
- Mehmet Karadağ
(Department of International Trade and Logistics, Çanakkale Onsekiz Mart University, Çanakkale 17200, Türkiye
Institute of Social Sciences, Istanbul University, Beyazıt, Fatih, Istanbul 34116, Türkiye)
- Veysi Başhan
(Department of Marine Engineering, İstanbul Technical University, Istanbul 34940, Türkiye
Maritime Clean Energy Research Laboratory (MarCERLab), İstanbul Technical University, Istanbul 34940, Türkiye)
- Yusuf Tarık Mutlu
(Department of Marine Engineering, İstanbul Technical University, Istanbul 34940, Türkiye
Maritime Clean Energy Research Laboratory (MarCERLab), İstanbul Technical University, Istanbul 34940, Türkiye)
- Cenk Kaya
(Department of Marine Engineering, İstanbul Technical University, Istanbul 34940, Türkiye
Maritime Clean Energy Research Laboratory (MarCERLab), İstanbul Technical University, Istanbul 34940, Türkiye
Chair of Powertrain Technologies, Technische Universität Berlin, 10587 Berlin, Germany)
- Muhammet Gul
(Department of Transportation and Logistics, Istanbul University, Istanbul 34940, Türkiye)
- Emre Akyuz
(Department of Maritime Transportation and Management Engineering, Istanbul Technical University, Istanbul 34940, Türkiye
Industrial Data Analytics and Decision Support Systems Center, Azerbaijan State University of Economics, Baku 1001, Azerbaijan)
Abstract
Improving ship energy efficiency has become a critical priority for reducing fuel consumption and meeting international decarbonization targets. In this study, eight major groups of energy efficiency improvement systems—including wind and solar energy technologies, hull and propeller modifications, air lubrication, green propulsion options, waste heat recovery, and engine power limitation—were evaluated against seven critical success factors. A hybrid neutrosophic fuzzy multi-criteria decision-making (MCDM) framework was employed to capture expert uncertainty and prioritize alternatives. Neutrosophic fuzzy sets were adopted because they more comprehensively represent uncertainty—simultaneously modeling truth, indeterminacy, and falsity, providing superior capability to address expert ambiguity compared with classical fuzzy, intuitionistic fuzzy, gray, or other uncertainty-handling frameworks. Trapezoidal Neutrosophic Fuzzy Analytic Hierarchy Process (AHP) (TNF-AHP) was first applied to determine the relative importance of the criteria, highlighting fuel savings and cost-effectiveness as dominant factors with 38% weight. Subsequently, the Fuzzy Combined Compromise Solution (F-CoCoSo) method was used to rank the alternatives. Results indicate that solar energy systems and wind-assisted propulsion consistently rank highest (with 3.35 and 2.92 performance scores) across different scenarios, followed by green propulsion technologies, while waste heat recovery and engine power limitation show lower performance. These findings not only provide a structured assessment of current technological options, but also offer actionable guidance for shipowners, operators, and policymakers seeking to prioritize investments in sustainable maritime operations.
Suggested Citation
Hakan Demirel & Mehmet Karadağ & Veysi Başhan & Yusuf Tarık Mutlu & Cenk Kaya & Muhammet Gul & Emre Akyuz, 2025.
"Hybrid Neutrosophic Fuzzy Multi-Criteria Assessment of Energy Efficiency Enhancement Systems: Sustainable Ship Energy Management and Environmental Aspect,"
Sustainability, MDPI, vol. 18(1), pages 1-30, December.
Handle:
RePEc:gam:jsusta:v:18:y:2025:i:1:p:166-:d:1824825
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