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Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure

Buildings (Basel), 2022-07, Vol.12 (7), p.1059 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2075-5309 ;EISSN: 2075-5309 ;DOI: 10.3390/buildings12071059

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Title:
Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure
Author: Matić, Bojan ; Marinković, Milan ; Jovanović, Stanislav ; Sremac, Siniša ; Stević, Željko
Subjects: Algorithms ; Civil engineering ; Comparative analysis ; Concrete ; construction ; Construction equipment ; Construction industry ; construction mechanization ; Correlation coefficient ; Correlation coefficients ; Costs ; D numbers ; Decision making ; Design ; Efficiency ; IMF SWARA ; Infrastructure ; Literature reviews ; Machinery ; Methods ; Multiple criterion ; Pavers ; Performance enhancement ; Performance evaluation ; Road construction ; road infrastructure ; Roads ; Roads & highways ; Rough MARCOS ; Sensitivity analysis
Is Part Of: Buildings (Basel), 2022-07, Vol.12 (7), p.1059
Description: The quality of road infrastructure largely depends on the quality of road construction and adequate construction machinery. In order to reduce uncertainties and improve the performance of road infrastructure, it is necessary to apply modern and appropriate construction machinery. The aim of this study was to create a novel integrated multi-criteria decision-making (MCDM) model for the selection of pavers for the middle category of roads. A total of 16 criteria were defined and then divided into four main groups, on the basis of which the performance of 12 pavers was evaluated. Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with D numbers (IMF D-SWARA) was extended to determine the significance of the criteria for the selection of construction machinery based on two groups of experts. Rough measurement of choices and their ranking as a compromise solution (R-MARCOS) was used to evaluate and rank the performance of construction machinery. The results show that three alternatives out of the set considered can satisfy defined requirements. After that, we performed a multi-phase validity test in which different values of criterion weights were simulated. A comparative analysis with seven other Rough MCDM methods was also created, and the Spearman’s correlation coefficient (SCC) and WS coefficient were calculated to determine the correlation of ranks for sensitivity analysis and comparative analysis. Thus, the obtained results were verified.
Publisher: Basel: MDPI AG
Language: English
Identifier: ISSN: 2075-5309
EISSN: 2075-5309
DOI: 10.3390/buildings12071059
Source: ROAD: Directory of Open Access Scholarly Resources
ProQuest Central
DOAJ Directory of Open Access Journals

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Intelligent Novel IMF D-SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure

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