| Title: | A fermatean fuzzy MCDM framework for green port transformation and heavy-duty forklift selection |
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| Authors: | ID Yalçın, Galip Cihan (Author)
ID Kara, Karahan (Author)
ID Gürol, Pınar (Author)
ID Babič, Matej (Author) |
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| Files: |  JEMSE_04.04_04.pdf (929,45 KB)
MD5: A35751498EFC7FC5C56D93B60658B5EB
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| Language: | English |
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| Work type: | Unknown |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FIŠ - Faculty of Information Studies in Novo mesto
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| Abstract: | The rapid growth of global trade has heightened the importance of efficient container handling, environmentally responsible operations, and high-performing equipment selection in sustaining the competitiveness of modern supply chains. Container Freight Stations (CFS) serve as critical operational hubs where loading, unloading, inspection, and temporary storage activities are conducted, thereby requiring equipment capable of safely and efficiently handling heavy-tonnage cargo while aligning with green port transformation goals. Forklifts, which constitute one of the core equipment groups in CFS yards, differ significantly in terms of lifting capacity, power systems, maneuverability, hydraulic performance, ergonomics, and environmental impact, transforming forklift selection into a complex, multi-dimensional decision problem shaped by both technical and Environmental, Social, and Governance (ESG)-oriented considerations. Incorrect equipment choices may lead to operational downtime, energy inefficiency, equipment failures, and occupational safety risks, particularly in operations involving loads exceeding 25 tons. To address these challenges, this study proposes a hybrid decision-making framework that integrates expert-driven fuzzy assessments with sustainability-based evaluation using the FF-Hamacher-MEREC-ARLON methodology. In the first stage, expert weights and criterion importance values were calculated through the FF-MEREC approach, while alternative forklifts were ranked using the FF-ARLON method in the second stage. Two sensitivity analysis scenarios were applied: one by modifying the tradeoff ratio within ARLON and the other by sequentially removing each criterion. In both scenarios, the fourth alternative consistently emerged as the most suitable option. Furthermore, comparative analyses using eight established MCDM techniques; ALWAS, AROMAN, ARTASI, MABAC, MARCOS, RAM, SAW, and WASPAS; demonstrated complete agreement with the proposed model, confirming the fourth alternative as the top-ranked choice. The findings highlight the robustness, reliability, and sustainability alignment of the proposed framework for high-stakes heavy-duty equipment selection in port-based logistics operations. |
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| Keywords: | Container Freight Stations, Fermatean fuzzy sets, Hamacher aggregation operator, MEREC, ARLON |
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| Submitted for review: | 25.09.2025 |
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| Article acceptance date: | 23.11.2025 |
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| Publication date: | 27.11.2025 |
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| Year of publishing: | 2025 |
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| Number of pages: | str. 269-283 |
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| Numbering: | Vol. 4, iss. 4 |
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| PID: | 20.500.12556/ReVIS-12901  |
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| COBISS.SI-ID: | 264007427 |
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| UDC: | 004.85:621.9 |
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| ISSN on article: | 2958-3527 |
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| DOI: | 10.56578/jemse040404 |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 12. 12. 2025;
Soavtorji: Karahan Kara, Pınar Gürol, Matej Babič;
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| Publication date in ReVIS: | 12.01.2026 |
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| Views: | 32 |
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| Downloads: | 0 |
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