Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS

Ayse Nur Karabayir; Ahmet Reha Botsali; Yildiz Kose; Emre Cevikcan

doi:10.1007/978-3-030-23756-1_60

Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS

Ayse Nur Karabayir^*, Ahmet Reha Botsali, Yildiz Kose, Emre Cevikcan

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

Abstract

Supplier selection is an important process for companies in the construction sector because of long-term projects and high cost. There are several criteria and alternatives to be considered in the construction industry and choosing the best multi-criteria decision‐making approach has become a critical step for selecting suppliers. Therefore, in this study, we analyze the problem of selecting the most convenient supplier for a construction company using two powerful multi-criteria decision‐making methods, Fuzzy AHP and Fuzzy TOPSIS. Due to the uncertainty embedded in problem’s nature and the ambiguity of the experts’ opinion, we prefer fuzzy methods. Various interviews were conducted with the experts at the companies in order to determine the criteria to be used in construction supplier evaluation. As a result of those interviews, 12 criteria that can be used for evaluating the alternative suppliers of the company were determined. This paper is comparing Fuzzy AHP and Fuzzy TOPSIS application results in a construction company in terms of determining the best supplier with respect to selected criteria. The contribution of this study is not only the application of the multi-criteria decision methodologies for supplier selection problem, but also it provides a comparison of two different multi-criteria decision making methods’ result.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
Publisher	Springer Verlag
Pages	481-487
Number of pages	7
ISBN (Print)	9783030237554
DOIs	https://doi.org/10.1007/978-3-030-23756-1_60
Publication status	Published - 2020
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey Duration: 23 Jul 2019 → 25 Jul 2019

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1029
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Country/Territory	Turkey
City	Istanbul
Period	23/07/19 → 25/07/19

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

Fuzzy AHP
Fuzzy TOPSIS
Supplier selection
Supply chain management

Access to Document

10.1007/978-3-030-23756-1_60

Cite this

Karabayir, A. N., Botsali, A. R., Kose, Y., & Cevikcan, E. (2020). Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference (pp. 481-487). (Advances in Intelligent Systems and Computing; Vol. 1029). Springer Verlag. https://doi.org/10.1007/978-3-030-23756-1_60

Karabayir, Ayse Nur ; Botsali, Ahmet Reha ; Kose, Yildiz et al. / Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS. Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A.Cagri Tolga. Springer Verlag, 2020. pp. 481-487 (Advances in Intelligent Systems and Computing).

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abstract = "Supplier selection is an important process for companies in the construction sector because of long-term projects and high cost. There are several criteria and alternatives to be considered in the construction industry and choosing the best multi-criteria decision‐making approach has become a critical step for selecting suppliers. Therefore, in this study, we analyze the problem of selecting the most convenient supplier for a construction company using two powerful multi-criteria decision‐making methods, Fuzzy AHP and Fuzzy TOPSIS. Due to the uncertainty embedded in problem{\textquoteright}s nature and the ambiguity of the experts{\textquoteright} opinion, we prefer fuzzy methods. Various interviews were conducted with the experts at the companies in order to determine the criteria to be used in construction supplier evaluation. As a result of those interviews, 12 criteria that can be used for evaluating the alternative suppliers of the company were determined. This paper is comparing Fuzzy AHP and Fuzzy TOPSIS application results in a construction company in terms of determining the best supplier with respect to selected criteria. The contribution of this study is not only the application of the multi-criteria decision methodologies for supplier selection problem, but also it provides a comparison of two different multi-criteria decision making methods{\textquoteright} result.",

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author = "Karabayir, {Ayse Nur} and Botsali, {Ahmet Reha} and Yildiz Kose and Emre Cevikcan",

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Karabayir, AN, Botsali, AR, Kose, Y & Cevikcan, E 2020, Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Advances in Intelligent Systems and Computing, vol. 1029, Springer Verlag, pp. 481-487, International Conference on Intelligent and Fuzzy Systems, INFUS 2019, Istanbul, Turkey, 23/07/19. https://doi.org/10.1007/978-3-030-23756-1_60

Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS. / Karabayir, Ayse Nur; Botsali, Ahmet Reha; Kose, Yildiz et al.
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A.Cagri Tolga. Springer Verlag, 2020. p. 481-487 (Advances in Intelligent Systems and Computing; Vol. 1029).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS

AU - Karabayir, Ayse Nur

AU - Botsali, Ahmet Reha

AU - Kose, Yildiz

AU - Cevikcan, Emre

PY - 2020

Y1 - 2020

N2 - Supplier selection is an important process for companies in the construction sector because of long-term projects and high cost. There are several criteria and alternatives to be considered in the construction industry and choosing the best multi-criteria decision‐making approach has become a critical step for selecting suppliers. Therefore, in this study, we analyze the problem of selecting the most convenient supplier for a construction company using two powerful multi-criteria decision‐making methods, Fuzzy AHP and Fuzzy TOPSIS. Due to the uncertainty embedded in problem’s nature and the ambiguity of the experts’ opinion, we prefer fuzzy methods. Various interviews were conducted with the experts at the companies in order to determine the criteria to be used in construction supplier evaluation. As a result of those interviews, 12 criteria that can be used for evaluating the alternative suppliers of the company were determined. This paper is comparing Fuzzy AHP and Fuzzy TOPSIS application results in a construction company in terms of determining the best supplier with respect to selected criteria. The contribution of this study is not only the application of the multi-criteria decision methodologies for supplier selection problem, but also it provides a comparison of two different multi-criteria decision making methods’ result.

AB - Supplier selection is an important process for companies in the construction sector because of long-term projects and high cost. There are several criteria and alternatives to be considered in the construction industry and choosing the best multi-criteria decision‐making approach has become a critical step for selecting suppliers. Therefore, in this study, we analyze the problem of selecting the most convenient supplier for a construction company using two powerful multi-criteria decision‐making methods, Fuzzy AHP and Fuzzy TOPSIS. Due to the uncertainty embedded in problem’s nature and the ambiguity of the experts’ opinion, we prefer fuzzy methods. Various interviews were conducted with the experts at the companies in order to determine the criteria to be used in construction supplier evaluation. As a result of those interviews, 12 criteria that can be used for evaluating the alternative suppliers of the company were determined. This paper is comparing Fuzzy AHP and Fuzzy TOPSIS application results in a construction company in terms of determining the best supplier with respect to selected criteria. The contribution of this study is not only the application of the multi-criteria decision methodologies for supplier selection problem, but also it provides a comparison of two different multi-criteria decision making methods’ result.

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KW - Supply chain management

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T3 - Advances in Intelligent Systems and Computing

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A2 - Kahraman, Cengiz

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A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

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PB - Springer Verlag

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Karabayir AN, Botsali AR, Kose Y, Cevikcan E. Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference. Springer Verlag. 2020. p. 481-487. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-23756-1_60

Supplier selection in a construction company using fuzzy AHP and fuzzy TOPSIS

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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