A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study

Hichem Brahmi; Maroua Ghram; Taicir Moalla Loukil

doi:doi:10.11648/j.aas.20220703.11

| Peer-Reviewed

A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study

Hichem Brahmi, Maroua Ghram, Taicir Moalla Loukil

Published in Advances in Applied Sciences (Volume 7, Issue 3)

Received: 3 June 2022 Accepted: 21 June 2022 Published: 26 July 2022

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Due to the increasingly competitive and globalized markets, companies seek to explore new sources of competitiveness by optimizing their supply chains and their relationships with their stakeholders. Studies show that the potential gains expected by a company that is solely interested in its internal management are very limited when compared to the potential gains throughout the supply chain. The Third Party Logistic (3PL) is chosen in this case to take charge of part or all of the logistics of the company. The terminology third party is due to the fact that is not the logistics provider who owns the products but participates in the supply chain at the points between the manufacturer and the user of a given product does. Currently, in a group decision-making context, choosing the most suitable 3PL supplier is a major challenge. In practice, some decision makers (DMs) intervene in the selection of 3PL suppliers, and each has their own perspective and wants to consider criteria that are not generally the same for all DMs. In this case study, we have coupled the Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method with ARAS-H (Hierarchical Additive Ratio Assessment). The main goal is to improve the decision-making process, build more efficient models and meet the needs of DMs. The proposed model is used to solve the 3PL problem of a company selling steel products.

Published in	Advances in Applied Sciences (Volume 7, Issue 3)
DOI	10.11648/j.aas.20220703.11
Page(s)	33-43
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Group Decision Support, 3PLs Suppliers, Fuzzy SWARA, ARAS-H, Multiple Criteria Decision Making

References

[1]	Ambrus, A., Greiner, B., & Pathak, P. (2009). “Group versus individual decision-making: Is there a shift”. Institute for Advanced Study. School of Social Science Economics Working Paper, Vol. 91.
[2]	Bozdag C. E., C. Kahraman and D. Ruan (2003). “Fuzzy group decision making for selection among computer integrated manufacturing systems”. Computers in Industry, Vol. 51 (1), PP. 13-29.
[3]	Büyüközkan, G., and Ciftci, G. (2012). “Evaluation of the green supply chain management practices: a fuzzy ANP approach”. Production Planning and Control, Vol. 23 (6), PP. 405-418.
[4]	Brahmi H. and Loukil M. T, (2021), “A New multicriteria decision support tool based on fuzzy SWARA and TOPSIS”, Multiple Criteria Decision Making (16), pp. 5-22.
[5]	Çalık, A. (2020). “A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the industry 4.0 era». https://doi.org/10.1007/s00500-020-05294-9, Vol. 25, PP. 2253–2265.
[6]	Chen Na, and X. Zeshui, (2015). “Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision-making problems.” Information Sciences, Vol. 292, PP. 175-197.
[7]	Chiang, K. (2009) “Weight determination for consistently ranking alternatives in multiple criteria decision analysis”, Applied Mathematical Modeling, Vol. 34 No. 7, PP. 1779-1787.
[8]	Devendra Ch. and Sh. Ravi (2014). “A goal programming model for joint decision making of inventory lot-size, supplier selection and carrier selection". Computers & Industrial Engineering, Vol. 71, PP. 1-9.
[9]	Ghram M. and Frikha H. M (2021). “ARAS-H: A ranking-based decision aiding method for hierarchically structured criteria”. RAIRO-Oper. Res, https://doi.org/10.1051/ro/2021083, Vol. 55, PP. 2035-2054.
[10]	Hosang J. (2017). “Evaluation of Third-Party Logistics Providers Considering Social Sustainability”. Asia Pacific School of Logistics, Inha University, 100 Inha-ro, Nam-gu, Incheon 402-751, Korea; hjung@inha.ac.kr. Vol. 9 (5), PP. 402-751.
[11]	Jain V., S. Wadhwa and S. G. Deshmukh (2007). “Supplier selection using fuzzy association rules mining approach.” International Journal of production Research, Vol. 41, PP. 1323-131.
[12]	Jain V. and L. Benyoucef, (2008). “Managing long supply chain networks: some emerging issues and challenges “, Journal of Manufacturing Technology Management, https://doi.org/10.1108/17410380810869923. Vol. 29 (4), PP. 469-496.
[13]	Eklund, P., Rusinowska, A., & De Swart, H. (2007). “Consensus reaching in committees”. European Journal of Operational Research, Vol. 178 (1), PP. 185-193.
[14]	Figuiera, J. and Roy, B. (2001) “Determining the weights of criteria in the ELECTRE type methods with a revised Simos procedure”, European Journal of Operational Research, Vol. 139, pp. 317-326.
[15]	Lin, R.-H. (2009). “An integrated FANP–MOLP for supplier evaluation and order allocation.” Applied Mathematical Modelling, doi: 10.1016/j.apm.2008.08.021, Vol. 33 (6), PP. 2730–2736.
[16]	Liu, X., Xu, Y., & Herrera, F. (2019). “Consensus model for large-scale group decision making based on fuzzy preference relation with self-confidence: Detecting and managing overconfidence behaviors”. Information Fusion. https://doi.org/10.1016/j.inffus.2019.03.001, Vol. 52, PP 245-256.
[17]	Kahraman C., C. Ufuk, and U Ziya. (2003). “Multi-criteria supplier selection using fuzzy AHP,” Logistics Information Management, Vol. 16 (6), PP. 382-394.
[18]	Karsak E. E. and M. Dursun (2014). “An integrated supplier selection methodology incorporating QFD and DEA with imprecise data.” Expert Systems with Applications, Vol. 41 (16), PP. 6957-4174.
[19]	Kumar K. A. (2014). “Revisiting the supplier selection problem: An integrated approach for group decision support.” Expert Systems with Applications: An International Journal, Vol. 41. PP 2762-2771.
[20]	Mafakheri, F., Breton, M., & Ghoniem, A. (2011).” Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach.” International Journal of Production Economics, Vol. 132 (1), PP. 52-57. doi: 10.1016/j.ijpe.2011.03.005.
[21]	Mavi, R. K., M. Goh, N. Zarbakhshnia, “Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry”, Int. J. Adv. Manuf. Technol. Vol. 91 (5–8) (2017) PP. 2401-2418.
[22]	Nakiboglu, G., & Bulgurcu, B. (2020). “Supplier selection in a Turkish textile company by using intuitionistic fuzzy decision-making”. The Journal of The Textile Institute, 1-11. https://doi:10.1080/00405000.2020.1747675, Vol. 112, PP. 322-332.
[23]	Nilay Y. G. and N. C. Demirel (2012), “Group decision making process for insurance company selection problem with extended VIKOR method under fuzzy environment”, Yıldız Technical University, Mechanical Faculty, Industrial Engineering Department, Bes_iktas_, Istanbul, Turkey. Vol. 39, PP. 3702-3707.
[24]	Pang JF, Liang JY. “Evaluation of the results of multi-attribute group decision-making with linguistic information”. Omega 2012; Vol. 40: PP. 294-301.
[25]	Rabiee, M., Aslani, B., & Rezaei, J. (2021). “A decision support system for detecting and handling biased decision-makers in multi criteria group decision-making problems”. Expert Systems with Applications, 171, 114597. doi: 10.1016/j.eswa.2021.114597, Vol. 171, PP. 114-597.
[26]	Rezaei, J. (2009) “Best-worst multi-criteria decision-making method”, Omega, Vol. 53, PP. 49-57.
[27]	Roszkowska, E. (2013) “Rank ordering criteria weighting methods– a comparative overview’, optimum studia ekonomiczne”, Vol. 5 No. 65, PP. 14-33.
[28]	Siskos, E. and Tsotsolas, N. (2015) ‘Elicitation of criteria importance weights through the Simos method: A robustness concern’, European Journal of Operational Research, Vol. 246 No. 2, PP. 543-553.
[29]	Şengül U., M. Eren, S. E. Shiraz and V. Gezder (2015). “Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey”. Renewable Energy Vol. 75, PP. 617-625.
[30]	Selçuk Perçin (2019), An Integrated Fuzzy SWARA and Fuzzy AD Approach for Outsourcing Provider Selection, Journal of Manufacturing Technology Management, https://doi.org/10.1108/JMTM-08-2018-0247.
[31]	Tanonkou G. A., L. Benyoucef and X. Xie, (2007). “A scenario analysis of a location problem with uncertain demand”. International Journal of Computer Applications in Technology, Vol. 32 (4), PP. 290-297.
[32]	Wei, G., Wei, C., & Guo, Y. (2021). “EDAS method for probabilistic linguistic multiple attribute group decision making and their application to green supplier selection”. Soft Computing, doi: 10.1007/s00500-021-05842-x, Vol. 25 (14), PP. 9045-9053.
[33]	Wu XL, Liao HC. “A consensus-based probabilistic linguistic gained and lost dominance score method”. European Journal of Operational Research 2019; Vol. 272 (3): PP. 1017-1027.
[34]	Yan J, Chaudhry PE, Chaudhry SS. (2003). “A model of decision support system based on case-based reasoning for third-party logistics evaluation”. Expert Systems; Vol. 20 (4), PP. 196-207.
[35]	Yu, G.-F., Li, D.-F., & Fei, W. (2018). “A novel method for heterogeneous multi-attribute group decision making with preference deviation”. Computers & Industrial Engineering, Vol. 124, PP. 58-64.

Cite This Article

Plain Text BibTeX RIS

APA Style

Hichem Brahmi, Maroua Ghram, Taicir Moalla Loukil. (2022). A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Advances in Applied Sciences, 7(3), 33-43. https://doi.org/10.11648/j.aas.20220703.11

Copy | Download

ACS Style

Hichem Brahmi; Maroua Ghram; Taicir Moalla Loukil. A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Adv. Appl. Sci. 2022, 7(3), 33-43. doi: 10.11648/j.aas.20220703.11

Copy | Download

AMA Style

Hichem Brahmi, Maroua Ghram, Taicir Moalla Loukil. A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Adv Appl Sci. 2022;7(3):33-43. doi: 10.11648/j.aas.20220703.11

Copy | Download

@article{10.11648/j.aas.20220703.11,
  author = {Hichem Brahmi and Maroua Ghram and Taicir Moalla Loukil},
  title = {A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study},
  journal = {Advances in Applied Sciences},
  volume = {7},
  number = {3},
  pages = {33-43},
  doi = {10.11648/j.aas.20220703.11},
  url = {https://doi.org/10.11648/j.aas.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20220703.11},
  abstract = {Due to the increasingly competitive and globalized markets, companies seek to explore new sources of competitiveness by optimizing their supply chains and their relationships with their stakeholders. Studies show that the potential gains expected by a company that is solely interested in its internal management are very limited when compared to the potential gains throughout the supply chain. The Third Party Logistic (3PL) is chosen in this case to take charge of part or all of the logistics of the company. The terminology third party is due to the fact that is not the logistics provider who owns the products but participates in the supply chain at the points between the manufacturer and the user of a given product does. Currently, in a group decision-making context, choosing the most suitable 3PL supplier is a major challenge. In practice, some decision makers (DMs) intervene in the selection of 3PL suppliers, and each has their own perspective and wants to consider criteria that are not generally the same for all DMs. In this case study, we have coupled the Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method with ARAS-H (Hierarchical Additive Ratio Assessment). The main goal is to improve the decision-making process, build more efficient models and meet the needs of DMs. The proposed model is used to solve the 3PL problem of a company selling steel products.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study
AU  - Hichem Brahmi
AU  - Maroua Ghram
AU  - Taicir Moalla Loukil
Y1  - 2022/07/26
PY  - 2022
N1  - https://doi.org/10.11648/j.aas.20220703.11
DO  - 10.11648/j.aas.20220703.11
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 33
EP  - 43
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20220703.11
AB  - Due to the increasingly competitive and globalized markets, companies seek to explore new sources of competitiveness by optimizing their supply chains and their relationships with their stakeholders. Studies show that the potential gains expected by a company that is solely interested in its internal management are very limited when compared to the potential gains throughout the supply chain. The Third Party Logistic (3PL) is chosen in this case to take charge of part or all of the logistics of the company. The terminology third party is due to the fact that is not the logistics provider who owns the products but participates in the supply chain at the points between the manufacturer and the user of a given product does. Currently, in a group decision-making context, choosing the most suitable 3PL supplier is a major challenge. In practice, some decision makers (DMs) intervene in the selection of 3PL suppliers, and each has their own perspective and wants to consider criteria that are not generally the same for all DMs. In this case study, we have coupled the Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method with ARAS-H (Hierarchical Additive Ratio Assessment). The main goal is to improve the decision-making process, build more efficient models and meet the needs of DMs. The proposed model is used to solve the 3PL problem of a company selling steel products.
VL  - 7
IS  - 3
ER  -

Copy | Download

Author Information

Hichem Brahmi

Faculty of Economics and Management of Sfax, University of Sfax, Sidi Bouzid, Tunisia
Maroua Ghram

Faculty of Economics and Management of Sfax, University of Sfax, Sfax, Tunisia
Taicir Moalla Loukil

Faculty of Economics and Management of Sfax, University of Sfax, Sfax, Tunisia

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Hichem Brahmi, Maroua Ghram, Taicir Moalla Loukil. (2022). A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Advances in Applied Sciences, 7(3), 33-43. https://doi.org/10.11648/j.aas.20220703.11

Copy | Download

ACS Style

Hichem Brahmi; Maroua Ghram; Taicir Moalla Loukil. A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Adv. Appl. Sci. 2022, 7(3), 33-43. doi: 10.11648/j.aas.20220703.11

Copy | Download

AMA Style

Hichem Brahmi, Maroua Ghram, Taicir Moalla Loukil. A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study. Adv Appl Sci. 2022;7(3):33-43. doi: 10.11648/j.aas.20220703.11

Copy | Download

@article{10.11648/j.aas.20220703.11,
  author = {Hichem Brahmi and Maroua Ghram and Taicir Moalla Loukil},
  title = {A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study},
  journal = {Advances in Applied Sciences},
  volume = {7},
  number = {3},
  pages = {33-43},
  doi = {10.11648/j.aas.20220703.11},
  url = {https://doi.org/10.11648/j.aas.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20220703.11},
  abstract = {Due to the increasingly competitive and globalized markets, companies seek to explore new sources of competitiveness by optimizing their supply chains and their relationships with their stakeholders. Studies show that the potential gains expected by a company that is solely interested in its internal management are very limited when compared to the potential gains throughout the supply chain. The Third Party Logistic (3PL) is chosen in this case to take charge of part or all of the logistics of the company. The terminology third party is due to the fact that is not the logistics provider who owns the products but participates in the supply chain at the points between the manufacturer and the user of a given product does. Currently, in a group decision-making context, choosing the most suitable 3PL supplier is a major challenge. In practice, some decision makers (DMs) intervene in the selection of 3PL suppliers, and each has their own perspective and wants to consider criteria that are not generally the same for all DMs. In this case study, we have coupled the Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method with ARAS-H (Hierarchical Additive Ratio Assessment). The main goal is to improve the decision-making process, build more efficient models and meet the needs of DMs. The proposed model is used to solve the 3PL problem of a company selling steel products.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - A New Group Decision Making Approach with Fuzzy SWARA and ARAS-H for Selecting Steel Products Suppliers: A Case Study
AU  - Hichem Brahmi
AU  - Maroua Ghram
AU  - Taicir Moalla Loukil
Y1  - 2022/07/26
PY  - 2022
N1  - https://doi.org/10.11648/j.aas.20220703.11
DO  - 10.11648/j.aas.20220703.11
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 33
EP  - 43
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20220703.11
AB  - Due to the increasingly competitive and globalized markets, companies seek to explore new sources of competitiveness by optimizing their supply chains and their relationships with their stakeholders. Studies show that the potential gains expected by a company that is solely interested in its internal management are very limited when compared to the potential gains throughout the supply chain. The Third Party Logistic (3PL) is chosen in this case to take charge of part or all of the logistics of the company. The terminology third party is due to the fact that is not the logistics provider who owns the products but participates in the supply chain at the points between the manufacturer and the user of a given product does. Currently, in a group decision-making context, choosing the most suitable 3PL supplier is a major challenge. In practice, some decision makers (DMs) intervene in the selection of 3PL suppliers, and each has their own perspective and wants to consider criteria that are not generally the same for all DMs. In this case study, we have coupled the Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method with ARAS-H (Hierarchical Additive Ratio Assessment). The main goal is to improve the decision-making process, build more efficient models and meet the needs of DMs. The proposed model is used to solve the 3PL problem of a company selling steel products.
VL  - 7
IS  - 3
ER  -

Copy | Download