Mobile Crane Selection in Project Logistics Operations Using Best and Worst Method (bwm) and Fuzzy Measurement of Alternatives and Ranking According To Compromise Solution (marcos)
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Date
2023
Authors
Gorcun, Omer Faruk
Dogan, Gurkan
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Publisher
Elsevier
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Abstract
Statistics on occupational accidents published by international organizations show that mobile cranes are the riskiest heavy equipment among all crane types. The most significant reason for these crane accidents is the decision-makers' wrong selection of mobile cranes. Making misevaluations and selecting improper mobile cranes can cause many problems besides mobile crane accidents. In addition, selecting a mobile crane is a highly complicated decision-making problem, as there are many conflicting criteria and uncertainties. Besides, no commonly accepted criteria set is used to solve this decision-making problem in the literature. The current paper proposes the fuzzy BWM (Best and Worst Method) and fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) combination as a robust and practical decision-making tool that can overcome many complicated ambiguities. The suggested model has been applied to solve a mobile crane se-lection problem encountered by a large-scale project logistics and heavy transport company in Turkey. The acquired outcomes demonstrated that technical criteria are more influential than economic and quality criteria. The criterion Maximum hoist height in the technical criteria group is the most influential factor in selecting the best mobile crane option. In addition, the A1 Brand-L. 4.2 is the most appropriate alternative to meet the company's requirements. Finally, a comprehensive sensitivity analysis performed to test the validity and applicability of the model approves the robustness of the model.
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Keywords
Optimization, Criteria, Mobile crane selection, Fuzzy BWM, Optimization, Fuzzy MARCOS, Criteria, Project logistics
Turkish CoHE Thesis Center URL
Fields of Science
Citation
6
WoS Q
Q1
Scopus Q
Q1
Source
Automation in Construction
Volume
147