Decision Making Through the Fuzzy TOPSIS Method
Contractor Selection in Construction Projects
Keywords:Construction Projects, Contractor, Fuzzy Decision Making, AHP, TOPSIS
Construction contractors have a great role in terms of operation work properly in construction project management. An effective contractor selection is most important to the success of any construction projects. Contractor selection is a multi criteria decision making problem which includes qualitative and quantitative characteristics. For the contractor selection problem, this study proposes a combined decision approach, which employs analytic hierarchy process (AHP) and Fuzzy Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS) methods. In the proposed approach, AHP is used to determine the weights of selection criteria, and Fuzzy TOPSIS is used to select appropriate contractor alternative. Additionally, a real case study in construction industry is presented to illustrate the application of the proposed approach.
Abbasianjahromi, H., Rajaie, H., & Shakeri, E. (2013). A Framework for Subcontractor Selection in the Construction Industry, Journal of Civil Engineering and Management, 19, 2, 158-168, DOI: 10.3846/13923730.2012.743922
Albayrak, E., & Erensal, Y. C. (2004). Using Analytic Hierarchy Process (AHP) to Improve Human Performance. An Application of Multiple Criteria Decision Making Problem, Journal of Intelligent Manufacturing, 15, 491-503.
Alcan, P., & Basligil, H. (2011). A Facility Location Selection Problem by Fuzzy TOPSIS, Proceedings of 15th International Research/Expert Conference ”Trends in the Development of Machinery and Associated Technology” TMT 2011, 329-332.
Allahverdi, N. (2005). Bulanık Mantık ve Sistemler, http://farabi.selcuk.edu.tr/egitim/bulanik/bulanik.htm
Apak, S., Vayvay, Ö., & Feyzioğlu, P (2013). A Decision Making Model for the Evaluation of Supply Chain Execution and Management Systems, International Journal of Computational Intelligence Systems, 6, 2, 293-306, DOI:10.1080/18756891.2013.769767
Barrie, D. S., & Paulson, B. C. (1992). Professional Construction Management: Including CM, Design-Construct, and General Contracting. McGraw-Hill.
Beyazid, O., (2005). Use of AHP in Decision-Making for Flexible Manufacturıng Systems, Journal of Manufacturing Technology Management, 16, 7, 808-819, DOI: 10.1108/17410380510626204
Cavallaro, F. (2010). Fuzzy TOPSIS Approach for Assessing Thermal-Energy Storage in Concentrated Solar Power (CSP) Systems, Applied Energy, 87, 496-503, DOI:10.1016/j.apenergy.2009.07.009
Chen, C. T. (2000). Extensions of the TOPSIS for Group Decision-Making Under Fuzzy Environment. Fuzzy sets and Systems, 114, 1, 1-9, DOI:10.1016/S0165-0114(97)00377-1
Chen, C. T., & Lin, C. T., Huang, S. F. (2006). A Fuzzy Approach for Supplier Evaluation and Selection in Supply Chain Management. International Journal of Production Economics, 102, 2, 289-301, DOI:10.1016/j.ijpe.2005.03.009
Cheng, C. H. (1999). Evaluating Weapon Systems Using Ranking Fuzzy Numbers, Fuzzy Sets and Systems, 107, 1, 25-35, DOI:10.1016/S0165-0114(97)00348-5
Chu, T. C. (2002). Facility Location Selection Using Fuzzy TOPSIS Under Group Decisions. Int. Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10, 687-701, DOI: 10.1142/S0218488502001739
Çiftçioğlu, B. (2013). İnşaat Sektöründe AHP Yöntemiyle Yüklenici Seçimi: Bir Konut Projesinde Uygulama, İstanbul Teknik Üniversitesi FBE Yüksek Lisans Tezi.
Dağdeviren, M., Yavuz, S. & Kılınç, N. (2009). Weapon Selection Using the AHP and TOPSIS Methods under Fuzzy Environment. Expert Systems with Applications, 36, 8143-8151, DOI:10.1016/j.eswa.2008.10.016
Darvish, M., Yasaei, M., & Saeedi, A. (2009). Application of the Graph Theory and Matrix Methods to Contractor Ranking. International Journal of Project Management, 27, 6, 610-619, DOI:10.1016/j.ijproman.2008.10.004
Dinçer, H., & Görener, A. (2011). Analitik Hiyerarşi Süreci ve VIKOR Tekniği ile Dinamik Performans Analizi: Bankacılık Sektöründe Bir Uygulama, İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19, 109-127.
Ebrahimnejad, S., & Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., Vahdani, B. (2012). A Novel Two-phase Group Decision Making Approach for Construction Project Selection in A Fuzzy Environment. Applied Mathematical Modelling, 36, 9, 4197-4217, DOI:10.1016/j.apm.2011.11.050
Eleren, A., & Ersoy, M. (2007). Mermer Blok Kesim Yöntemlerinin Bulanık TOPSIS Yöntemiyle Değerlendirilmesi, Madencilik, 46, 3, 9-22.
Fang, L., & Hipel, K. W., Kilgour, D. M. (1993). Interactive Decision Making: The Graph Model For Conflict Resolution, Vol. 3, John Wiley & Sons.
Fong, P. S. W., & Choi, S. K. Y. (2000). Final Contractor Selection using the Analytical Hierarchy Process. Construction Management & Economics, 18, 5, 547-557, DOI: 10.1080/014461900407356
Hatush, Z., & Skitmore, M. (1997). Criteria for Contractor Selection. Construction Management & Economics, 15, 1, 19-38, DOI:10.1080/014461997373088
Hatush, Z., & Skitmore, M. (1998). Contractor Selection using Multicriteria Utility Theory: An Additive Model. Building And Environment, 33, 2, 105-115, DOI:10.1016/S0360-1323(97)00016-4
Huang, X. (2011). An Analysis of the Selection of Project Contractor in the Construction Management Process. International Journal of Business and Management, 6, 3, 184-189.
Hwang, C. L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Application, Springer Publications, Berlin.
Jaskowski, P., Biruk, S., & Bucon, R. (2010). Assessing Contractor Selection Criteria Weights with Fuzzy AHP method Application in Group Decision Environment. Automation in Construction, 19, 2, 120-126, DOI:10.1016/j.autcon.2009.12.014
Kaptanoğlu, D., & Özok, A. F. (2010). Akademik Performans Değerlendirm3esi için Bir Bulanık Model. İTÜ Dergisi/d, 5, 1, 193-204.
Nieto-Morote, A., & Ruz-Vila, F. (2012). A Fuzzy Multi-Criteria Decision-Making Model For Construction Contractor Prequalification, Automation in Construction, 25, 8-19, DOI:10.1016/j.autcon.2012.04.004
Polat, G. (2015). Subcontractor Selection using the Integration of the AHP and PROMETHEE methods, Journal of Civil Engineering and Management, DOI: 10.3846/13923730.2014.948910.
Rençber, Ö. F., & Kazan, H. (2014). Büyük Çaplı Projelerde Taşeron Firma Seçiminde Teklif Değerlendirme: Analitik Hiyerarşi Süreci Yöntemi İle Karar Verme, International Journal of Social Science Research, 3, 1, 11-24.
Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning Priority Setting. McGraw Hill, New York.
Saaty, T. L. (1990). How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48, 9-26.
Saaty, T. L. (2008). Decision Making with the Analytic Hierarchy Process. International Journal of Service Sciences, 1, 1, 83-98.
Singh, D., & Tiong, R. L. (2005). A Fuzzy Decision Framework for Contractor Selection. Journal of Construction Engineering and Management, 131, 1, 62-70, DOI: 10.1061/(ASCE)0733-9364(2005)131:1(62)
Singh, R. K., & Benyoucef, L. (2011). A Fuzzy TOPSIS Based Approach for E-Sourcing, Engineering Applications of Artificial Intelligence, 24, 437-448, DOI:10.1016/j.engappai.2010.09.006
Shanian, A., & Savadogo, O. (2006). TOPSIS Multiple-Criteria Decision Support Analysis for Material Selection of Metallic Bipolar Plates for Polymer Electrolyte Fuel Cell, Journal of Power Sources, 159, 1095-1104, DOI:10.1016/j.jpowsour.2005.12.092
Shahanaghi, K., & Yazdian, S. A. (2009). Vendor Selection Using a New Fuzzy Group TOPSIS Approach, Journal of Uncertain Systems, 3, 3, 221-231.
Shyjith, K., Ilangkumaran, M., & Kumanan, S. (2008). Multi-Criteria Decision-Making Approach to Evaluate Optimum Maintenance Strategy in Textile Industry, Journal of Quality in Maintenance Engineering, 14, 4, 375-386, DOI:10.1108/13552510810909975
Şen, Z. (2001). Bulanık Mantık ve Modelleme Ilkeleri. Bilge Kültür Sanat, İstanbul.
Topçu, Y. I. (2004). A Decision Model Proposal for Construction Contractor Selection in Turkey. Building and Environment, 39, 4, 469-481, DOI:10.1016/j.buildenv.2003.09.009
Torlak, G., Sevkli, M., Sanal, M., & Zaim, S. (2011). Analyzing Business Competition by Using Fuzzy TOPSIS Method: An Example of Turkish Domestic Airline Industry, Expert Systems with Applications, 38, 3396-3406, DOI:10.1016/j.eswa.2010.08.125
Zadeh, L. A. (1975). The Concept of A Linguistic Variable and Its Application to Approximate Reasoning-I, Information Sciences, 8, 3, 199-249, DOI:10.1016/0020-0255(75)90036-5
Zavadskas, E. K., Turskis, Z., & Tamošaitiene, J. (2008). Contractor Selection of Construction in a Competitive Environment. Journal of Business Economics and Management, 9, 3, 181-187, DOI: 10.3846/1611-1699.2008.9.181-187
How to Cite
Copyright (c) 2016 A. Oben Sabuncuoglu, Ali Gorener
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to IJRBS agree to publish their articles under the Creative Commons Attribution- 4.0 International (CC BY 4.0) license, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit, that the work is not used for commercial purposes, and that in the event of reuse or distribution, the terms of this license are made clear. Authors retain the copyright of their work, with first publication rights granted to IJRBS. However, authors are required to transfer copyrights associated with commercial use to the Publisher. The authors agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal
Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other languages, without the written consent of the Publisher. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication