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An integrated intelligent system for construction industry: a case study of raised floor material

    Abdullah Cemil Ilce Affiliation
    ; Kadir Ozkaya Affiliation

Abstract

This paper aims to introduce a quantitative method to builders for the most appropriate material selections based on multiple attributes and integrate decision group member opinions throughout bidding process. In this respect, a new model used together with the Analytic Hierarchy Process (AHP) and fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), multi-criteria decision methods are proposed. In a real decision process, there are many uncertainties and ambiguities. In fact decision makers cannot always provide practical guidelines and especially precise judgments due to time limitations. The intelligent model proposed demonstrates that the AHP and fuzzy MOORA approach can not only be used easily to imitate the decision duration in the material selection but also the results obtained from this work provide contractors valuable insight into the material selection problem. At the same time, the quantitative analysis method based on the appropriately raised floor materials along the bidding process enables the builders to use their restricted resources more expeditiously and enhances considerably the possibility of winning agreement, as one of the most striking points deduced from the present study. In short, the model with AHP and fuzzy MOORA approaches can assist the builders to improve resolutions for the bidding.

Keyword : material selection, the cost of purchasing, intelligent selection system, reduce workload, AHP, fuzzy MOORA

How to Cite
Ilce, A. C., & Ozkaya, K. (2018). An integrated intelligent system for construction industry: a case study of raised floor material. Technological and Economic Development of Economy, 24(5), 1866-1884. https://doi.org/10.3846/20294913.2017.1334242
Published in Issue
Oct 1, 2018
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Akhavan, P.; Barak, S.; Maghsoudlou, S.; Antuchevičienė, J. 2015. FQSPM-SWOT for strategic alliance planning and partner selection; case study in a holding car manufacturer company, Technological and Economic Development of Economy 21(2): 165–185. https://doi.org/10.3846/20294913.2014.965240

Akkaya, G.; Turanoğlu, B.; Öztaş, S. 2015. An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing, Expert Systems with Applications 42(24): 9565–9573. https://doi.org/10.1016/j.eswa.2015.07.061

Arbel, A.; Orgler, Y. E. 1990. An application of the AHP to bank strategic planning: the mergers and acquisitions process, European Journal of Operational Research 48(1): 27–37. https://doi.org/10.1016/0377-2217(90)90058-J

Archana, M.; Sujatha, V. 2012. Application of fuzzy MOORA and GRA in multi criterion decision making problems, International Journal of Computer Applications 53(9): 46–50. https://doi.org/10.5120/8452-2249

Balezentis, T. 2011. A farming efficiency estimation model based on fuzzy Multimoora, Management Theory and Studies for Rural Business and Infrastructure Development 5(29): 43–52.

Balezentis, A.; Balezentis, T.; Brauers, W. K. M. 2012. Multimoora-FG: a multi-objective decision making method for linguistic reasoning with an application to personnel selection, Informatica 23(2): 173–190.

Brauers, W. K. 2004. Optimization methods for a stakeholder society: a revolution in economic thinking by multi-objective optimization. Boston: Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4419-9178-2

Brauers, W. K. M.; Zavadskas, E. K. 2006. The MOORA method and its application to privatization in a transition economy, Control and Cybernetics 35(2): 445–469.

Brauers, W. K. M.; Zavadskas, E. K. 2012. Robustness of MULTIMOORA: a method for multi- objective optimization, Informatica 23(1): 1–25.

Chakraborty, S. 2010. Application of the MOORA method for decision making in manufacturing environment, International Journal of Advanced Manufacturing Technology 54(9): 1155–1166.

Chang, S. C.; Tsai, P. H. 2016. A hybrid financial performance evaluation model for wealth management banks following the global financial crisis, Technological and Economic Development of Economy 22(1): 21–46. https://doi.org/10.3846/20294913.2014.986771

Chang, Y. H.; Yeh, C. H. 2002. A survey analysis of service quality for domestic airlines, European Journal of Operational Research 139(1): 166–177. https://doi.org/10.1016/S0377-2217(01)00148-5

Chang, Y. H.; Yeh, C. H.; Wang, S. Y. 2007. A survey and optimization-based evaluation of development strategies for the air cargo industry, International Journal of Production Economics 106(2): 550–562. https://doi.org/10.1016/j.ijpe.2006.06.016

Chen, C. T. 2000. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems 114(1): 1–9. https://doi.org/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. https://doi.org/10.1016/j.ijpe.2005.03.009

Cheng, C. H. 1997. Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function, European Journal of Operational Research 96(2): 343–350. https://doi.org/10.1016/S0377-2217(96)00026-4

Dağdeviren, M.; Eren, T. 2001. Analytical hierarchy process and use of 0-1 goal programming methods in selecting supplier firm, Journal of the Faculty of Engineering and Architecture of Gazi University 16(2): 41–52 (In Turkish).

Dağdeviren, M.; Yavuz, S.; Kılınç, N. 2009. Weapon selection using the AHP and TOPSIS methods under fuzzy environment, Expert Systems with Applications 36(4): 8143–8151. https://doi.org/10.1016/j.eswa.2008.10.016

Dey, B.; Bairagi, B.; Sarkar, B.; Sanyal, S. 2012. A MOORA based fuzzy multi criteria decision making approach for supply chain strategy selection, International Journal of Industrial Engineering Computations 3(4): 649–662. https://doi.org/10.5267/j.ijiec.2012.03.001

Deng, X.; Hu, Y.; Deng, Y.; Mahadevan, S. 2014. Supplier selection using AHP methodology extended by D numbers, Expert Systems with Applications 41(1): 156–167. https://doi.org/10.1016/j.eswa.2013.07.018

Ding, J. F.; Liang, G. S. 2005. Using fuzzy MCDM to select partners of strategic alliances for liner shipping, Information Sciences 173(1–3): 197–225. https://doi.org/10.1016/j.ins.2004.07.013

Douligeris, C.; Pereira I. J. 1994. A telecommunications quality study using the analytic hierarchy process, IEEE Journal on Selected Areas in Communications 12(2): 241–250. https://doi.org/10.1109/49.272873

Ecer, F. 2014. A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case, Technological and Economic Development of Economy 20(4): 758–782. https://doi.org/10.3846/20294913.2014.915596

Ghodsypour, S. H.; Brien, C. O. 1998. A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming, International Journal of Production Economics 56–57: 199–212. https://doi.org/10.1016/S0925-5273(97)00009-1

Ho, W. 2008. Integrated analytic hierarchy process and its applications – a literature review, European Journal of Operational Research 186(1): 211–228. https://doi.org/10.1016/j.ejor.2007.01.004

Ho, W.; Xu, X.; Dey, P. K. 2010. Multi-criteria decision making approaches for supplier evaluation and selection: a literature review, European Journal of Operational Research 202(1): 16–24. https://doi.org/10.1016/j.ejor.2009.05.009

Ilce, A.C. 2007. Investigation of physical mechanical properties of raised flooring materials used in computerized spaces, and determination of their effects on space design: PhD thesis. Hacettepe University (In Turkish).

Kahraman, C.; Cebeci, U.; Ulukan, Z. 2003. Multi-criteria supplier selection using fuzzy AHP, Logistics Information Management 16(6): 382–394. https://doi.org/10.1108/09576050310503367

Kahraman, C.; Beskese, A.; Ruan, D. 2004. Measuring flexibility of computer integrated manufacturing systems using fuzzy cash flow analysis, Information Sciences 168(1–4): 77–94. https://doi.org/10.1016/j.ins.2003.11.004

Karsak, E. E.; Tolga, E. 2001. Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments, International Journal of Production Economics 69(1): 49–64. https://doi.org/10.1016/S0925-5273(00)00081-5

Karande, P.; Chakraborty, S. 2012. A fuzzy-MOORA approach for ERP system selection, Decision Science Letters 1(1): 11–21. https://doi.org/10.5267/j.dsl.2012.07.001

Kaya, T., Kahraman, C. 2011. A fuzzy approach to e-bankıng websıte qualıty assessment based on an integrated AHP-ELECTRE method, Technological and Economic Development of Economy 17(2): 313–334. https://doi.org/10.3846/20294913.2011.583727

Lai, V. S.; Trueblood, R. P.; Wong, B. K. 1999. Software selection: a case study of the application of the analytical hierarchical process to the selection of a multimedia authoring system, Information & Management 36(4): 221–232. https://doi.org/10.1016/S0378-7206(99)00021-X

Mandal, U. K.; Sarkar, B. 2012. Selection of best intelligent manufacturing system under fuzzy MOORA conflicting MCDM environment, International Journal of Engineering Technology and Advanced Engineering 2(9): 301–310.

Mansor, M. R.; Sapuan, S. M.; Zainudin, E. S.; Nuraini, A. A.; Hambali, A. 2013. Hybrid natural and glass fibers reinforced polymer composites material selection using Analytical Hierarchy Process for automotive brake lever design, Materials and Design 51: 484–492. https://doi.org/10.1016/j.matdes.2013.04.072

Oztaysi, B. 2014. A decision model for information technology selection using AHP integrated TOPSIS-Grey: the case of content management systems, Knowledge-Based Systems 70(C): 44–54. https://doi.org/10.1016/j.knosys.2014.02.010

Önüt, S.; Soner, S. 2008. Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment, Waste Management 28(9): 1552–1559. https://doi.org/10.1016/j.wasman.2007.05.019

Pourahmad, A.; Hosseini, A.; Banaitis, A.; Nasiri, H.; Banaitienė, N.; Tzeng, G. H. 2015. Combination of FUZZY-AHP and DEMANTEL-ANP with gis in a new hybrid MCDM model used for the selection of the best space for leisure in a blighted urban site, Technological and Economic Development of Economy 21(5): 773–796. https://doi.org/10.3846/20294913.2015.1056279

Raj, P. A.; Kumar, D. N. 1999. Ranking alternatives with fuzzy weights using maximizing set and minimizing set, Fuzzy Sets and Systems 105(3): 365–375. https://doi.org/10.1016/S0165-0114(97)00243-1

Saaty, T. L. 1990. How to make a decision: the analytic hierarchy process, European Journal of Operational Research 48(1): 9–26. https://doi.org/10.1016/0377-2217(90)90057-I

Saaty, T. L. 2008. Decision making with the analytic hierarchy process, International Journal of Services Sciences 1(1): 83–98. https://doi.org/10.1504/IJSSCI.2008.017590

Sivakumar, R.; Kannan, D.; Murugesan, P. 2015. Green vendor evaluation and selection using AHP and Taguchi loss functions in production outsourcing in mining industry, Resources Policy 46(1): 64–75. https://doi.org/10.1016/j.resourpol.2014.03.008

Stanujkic, D. 2013. An extension of the MOORA method for solving fuzzy decision making problems, Technological and Economic Development of Economy 19(1): 228–255. https://doi.org/10.3846/20294913.2013.880083

Tam, M. C. Y.; Tummala, V. M. R. 2001. An application of the AHP in vendor selection of a telecommunications system, OMEGA 29(2): 171–182. https://doi.org/10.1016/S0305-0483(00)00039-6

TS EN 323:1999. Wood- Based panels- Determination of Density. Turkish Standard. (In Turkish).

TS EN 12825:2003. Raised access floors. Turkish Standard. (In Turkish).

TS EN 438:2006. High-pressure decorative laminates (HPL) – Sheets based on thermosetting resins (Usually called laminates) – Part 1: Introduction and general information. Turkish Standard. (In Turkish).

TS EN 311:2005. Wood-based panels – Surface soundness – Test method. Turkish Standard. (In Turkish).

TS EN 1081:1998. Resilient floorcoverings-Determination of the electrical resistance. Turkish Standard. (In Turkish).

Uyan, M. 2013. GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey, Renewable and Sustainable Energy Reviews 28: 11–17. https://doi.org/10.1016/j.rser.2013.07.042

Vargas, L. G. 1990. An overview of the AHP and its application, European Journal of Operational Research 48(1): 2–8. https://doi.org/10.1016/0377-2217(90)90056-H

Vatansever, K.; Kazançoğlu, Y. 2014. Integrated usage of fuzzy multi criteria decision making techniques for machine selection problems and an application, International Journal of Business and Social Science 5(9): 12–24.

Wang, T. C.; Chang, T. H. 2007. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications 33(4): 870–880. https://doi.org/10.1016/j.eswa.2006.07.003

Wang, X.; Chan, H. K.; Lee, C. K. M.; Li, D. 2015. A hierarchical model for eco-design of consumer electronic products, Technological and Economic Development of Economy 21(1): 48–64. https://doi.org/10.3846/20294913.2013.876685

Xu, L.; Kumar, D. T.; Shankar, K. M.; Kannan, D.; Chen, G. 2013. Analyzing criteria and sub-criteria for the corporate social responsibility-based supplier selection process using AHP, The International Journal of Advanced Manufacturing Technology 68: 907–916. https://doi.org/10.1007/s00170-013-4952-7

Xu, Z. S.; Chen, J. 2007. An interactive method for fuzzy multiple attribute group decision making, Information Sciences 177(1): 248–263. https://doi.org/10.1016/j.ins.2006.03.001

Zadeh, L. A. 1965. Fuzzy sets, Information and Control 8(3): 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Zadeh, L. A. 1975. The concept of a linguistic variable and its application to approximate reasoning I, Information Sciences 8: 199–249. https://doi.org/10.1016/0020-0255(75)90036-5

Zahedi, F. 1987. A Utility approach to the AHP, Mathematical Modelling 9(3–5): 387–395. https://doi.org/10.1016/0270-0255(87)90497-0

Zimmerman, H. J. 1996. Fuzzy sets theory and its applications. Boston: Kluwer Academic Publishers. https://doi.org/10.1007/978-94-015-8702-0

Zolfani, S. H.; Chen, I. S.; Rezaeiniya, N.; Tamošaitienė, J. 2012. A hybrid MCDM model encompassing AHP and COPRAS-G methods for selecting company supplier in Iran, Technological and Economic Development of Economy 18(3): 529–543. https://doi.org/10.3846/20294913.2012.709472

Zviran, M. A. 1993. Comprehensive methodology for computer family selection, Journal Systems Software 22(1): 17–26. https://doi.org/10.1016/0164-1212(93)90119-I