Imperial College London
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ProfessorArnabMajumdar

Faculty of Engineering, Department of Civil and Environmental Engineering

Professor of Transport Risk and Safety
 
 
 
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Contact

 

+44 (0)20 7594 6037a.majumdar

 
 
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Assistant

 

Ms Maya Mistry +44 (0)20 7594 6100

 
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Location

 

604Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Rahman:2022:10.3390/buildings12070940,
author = {Rahman, AU and Saeed, M and Mohammed, MA and Majumdar, A and Thinnukool, O},
doi = {10.3390/buildings12070940},
journal = {Buildings},
pages = {1--20},
title = {Supplier selection through multicriteria decision-making algorithmic approach based on rough approximation of fuzzy hypersoft sets for construction project},
url = {http://dx.doi.org/10.3390/buildings12070940},
volume = {12},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The suppliers play a significant role in supply chain management. In supplier selection, factors like market-based exposure, community-based reputation, trust-based status, etc., must be considered, along with the opinions of hired experts. These factors are usually termed as rough information. Most of the literature has disregarded such factors, which may lead to a biased selection. In this study, linguistic variables in terms of triangular fuzzy numbers (TrFn) are used to manage such kind of rough information, then the rough approximations of the fuzzy hypersoft set (FHS-set) are characterized which are capable of handling such informational uncertainties. The FHS-set is more flexible as well as consistent as it tackles the limitation of fuzzy soft sets regarding categorizing parameters into their related sub-classes having their sub-parametric values. Based on these rough approximations, an algorithm is proposed for the optimal selection of suppliers by managing experts’ opinions and rough information collectively in the form of TrFn-based linguistic variables. To have a discrete decision, a signed distance method is employed to transform the TrFn-based opinions of experts into fuzzy grades. The proposed algorithm is corroborated with the help of a multi-criteria decision-making application to choose the best supplier for real estate builders. The beneficial facets of the put forward study are appraised through its structural comparison with few existing related approaches. The presented approach is consistent as it is capable to manage rough information and expert’s opinions about suppliers collectively by using rough approximations of FHS-set.
AU  - Rahman,AU
AU  - Saeed,M
AU  - Mohammed,MA
AU  - Majumdar,A
AU  - Thinnukool,O
DO  - 10.3390/buildings12070940
EP  - 20
PY  - 2022///
SN  - 2075-5309
SP  - 1
TI  - Supplier selection through multicriteria decision-making algorithmic approach based on rough approximation of fuzzy hypersoft sets for construction project
T2  - Buildings
UR  - http://dx.doi.org/10.3390/buildings12070940
UR  - https://www.mdpi.com/2075-5309/12/7/940
UR  - http://hdl.handle.net/10044/1/98220
VL  - 12
ER  -
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