Decision-making model for sustainable management of Australian community buildings: combined approach using analytical hierarchy process and neuro-fuzzy system

References

• Abdelgawad M, Fayek AR. 2010. Risk management in the construction industry using combined fuzzy fmea and fuzzy ahp. J Constr Eng Manage. 136(9):1028–1036.
   Web of Science ®Google Scholar
• Al Khalil MI. 2002. Selecting the appropriate project delivery method using AHP. Int J Project Manage. 20(6):469–474.
   Google Scholar
• Ayres RU. 2002. Resources, scarcity, technology, and growth. Fontainebleau, France: Insead.
   Google Scholar
• Baker D, Bridges D, Hunter R, Johnson G, Krupa J, Murphy J, Sorenson K. 2002. Guidebook to decision-making methods. Department of Energy. http://emiweb.inel.gov/Nissmg/Guidebook_2002.pdf.
   Google Scholar
• Bertoni M. 2019. Multi-criteria decision making for sustainability and value assessment in early pss design'. Sustainability. 11(7):1952.
   Web of Science ®Google Scholar
• Boonstra C, Pettersen TD. 2003. Tools for environmental assessment of existing buildings. Ind Environ. 26(2–3):80–83.
   Google Scholar
• Boussabaine A. 2001. Neurofuzzy modelling of construction projects’ duration I: principles'. Eng Constr Archit Man. 8(2):104–113.
   Google Scholar
• Bowles JB, Peláez CE. 1995. Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab Eng Syst Saf. 50(2):203–213.
   Web of Science ®Google Scholar
• Brundtland GH, World Commission on Environment and Development. 1987. Report of the world commission on environment and development: “our common future”: annex. New York (NY), United Nations: Oxford University Press.
   Google Scholar
• Buckley JJ. 1985. Fuzzy hierarchical analysis. Fuzzy Sets Syst. 17(3):233–247.
   Web of Science ®Google Scholar
• Carson JS. 2002. Model verification and validation. Paper presented at the Winter Simulation Conference.
   Google Scholar
• Cheng M-Y, Tsai H-C, Ko C-H, Chang W-T. 2008. Evolutionary fuzzy neural inference system for decision making in geotechnical engineering. J Comput Civ Eng. 22(4):272–280.
   Web of Science ®Google Scholar
• Cuadrado J, Zubizarreta M, Rojí E, García H, Larrauri M. 2015. Sustainability-related decision making in industrial buildings: an ahp analysis. Math Prob Eng. 2015:1–13.
   Web of Science ®Google Scholar
• Cuadrado J, Zubizarreta M, Rojí E, Larrauri M, Álvarez I. 2016. Sustainability assessment methodology for industrial buildings: three case studies. Civ Eng Environ Syst. 33(2):106–124.
   Web of Science ®Google Scholar
• Daly HE, Cobb JB, Jr, Cobb JB. 1994. For the common good: redirecting the economy toward community, the environment, and a sustainable future. Boston, MA: Beacon Press.
   Google Scholar
• Eckersley R. 1992. Environmentalism and political theory: toward an ecocentric approach. Albany, NY: Suny Press.
   Google Scholar
• Edirisinghe R, Setunge S, Zhang G, Wakefield R. 2012. Council building management practices, case studies and road ahead. In: Mathew J, Ma L, Tan A, Weijnen M, LEE J, editors. Engineering asset management and infrastructure sustainability. London: Springer; p. 165–179.
   Google Scholar
• Elkington J. 1997. Cannibals with forks: the triple bottom line of 21st century business. 1st ed. Oxford: Capstone Publishing Ltd.
   Google Scholar
• Fülöp J. 2005. Introduction to decision making methods. Budapest (Hungary): Computer and Automation Institute, Hungarian Academy of Sciences.
   Google Scholar
• Galamba KR, Nielsen SB. 2016. Towards sustainable public fm: collective building of capabilities. Facilities. 34(3–4):177–195.
   Web of Science ®Google Scholar
• Häkkinen T, Vesikari E, Pulakka S. 2007. Sustainable management of buildings. In: Braganca L, Pinheiro M, Jalali S, Mateus R, Amoeda R, Guedes MC, editors. Portugal sb07- sustainable construction, materials and practices: challenge of the industry for the new millennium. Amsterdam (Netherlands): IOS Press; p. 233–240.
   Google Scholar
• Harris R. 2012. Introduction to decision making, viewed 7 May. https://www.virtualsalt.com/crebook5.htm.
   Google Scholar
• Hart M. 2013. Sustainable measures, viewed 15 March. http://www.sustainablemeasures.com/node/42.
   Google Scholar
• Huang Y-H. 2010. Artificial neural network model of bridge deterioration. J Perform Constr Facil. 24(6):597–602.
   Web of Science ®Google Scholar
• Hwang CL, Lai YJ, Liu TY. 1993. A new approach for multiple objective decision making. Comput Oper Res. 20(8):889–899.
   Web of Science ®Google Scholar
• International Council for Research and Innovation in Building and Construction (CIB). 1999. Report publication 237: agenda 21 on sustainable construction. Rotterdam (Netherlands): Centre cientifique et Technique du Batiment (CSTB).
   Google Scholar
• IPWEA. 2009. Building condition & performance assessment guidelines. Australia: IPWEA-NAMS.AU.
   Google Scholar
• Jang J-SR. 1997. Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. 1st ed. Upper Saddle River (NJ): Prentice Hall.
   Google Scholar
• Jin X, Doloi H. 2009. Modelling risk allocation in privately financed infrastructure projects using fuzzy logic. Computer-Aided Civ Infrastruct Eng. 24(7):509–524.
   Web of Science ®Google Scholar
• Junghans A. 2013. Decision support model for energy-efficient improvement of entire building stocks. Facilities. 31(3–4):173–184.
   Google Scholar
• Kahraman C, Cebeci U, Ruan D. 2004. Multi-attribute comparison of catering service companies using fuzzy ahp: the case of turkey. Int J Prod Econ. 87(2):171–184.
   Web of Science ®Google Scholar
• Kahraman C, Ruan D, Doǧan I. 2003. Fuzzy group decision-making for facility location selection. Inf Sci. 157(1–4):135–153.
   Google Scholar
• Kalutara P, Zhang G, Setunge S, Wakefield R. 2017. Factors that influence Australian community buildings’ sustainable management. Eng Constr Archit Manage. 24(1):94–117.
   Web of Science ®Google Scholar
• Kalutara P, Zhang G, Setunge S, Wakefield R. 2018. Prioritising sustainability factors for Australian community buildings’ management using Analytical Hierarchy Process (AHP). Int J Strategic Property Manage. 24(1):37–50. 'vol
   Google Scholar
• Kalutara P. 2013. Development of an integrated decision-making model for the sustainable management of community buildings in Australia [PhD thesis]. Melbourne (Australia): RMIT University.
   Google Scholar
• Keeler M, Vaidya P. 2016. Fundamentals of integrated design for sustainable building. Hoboken (NJ): John Wiley & Sons.
   Google Scholar
• Lee J, Sanmugarasa K, Blumenstein M, Loo Y-C. 2008. Improving the reliability of a bridge management system (bms) using an ann-based backward prediction model (bpm). Autom Constr. 17(6):758–772.
   Web of Science ®Google Scholar
• Mao H. 1999. Estimating labour productivity using fuzzy set theory [Masters thesis]. Edmonton: University of Alberta.
   Google Scholar
• McArthur JJ. 2015. A building information management (BIM) framework and supporting case study for existing building operations, maintenance and sustainability. Proc Eng. 118:1104–1111.
   Google Scholar
• McDermot E, Agdas D, Rodríguez Díaz CR, Rose T, Forcael E. 2020. Improving performance of infrastructure projects in developing countries: an Ecuadorian case study. Int J Constr Manage. 1–15. https://doi.org/10.1080/15623599.2020.1797985.
   Google Scholar
• McDulling JJ. 2006. Towards the development of transition probability matrices in the markovian model for the predicted service life of buildings [PhD thesis]. Pretoria: University of Pretoria.
   Google Scholar
• McShane I. 2006. Social value and the management of community infrastructure. Aust J Pub Admin. 65(4):82–96.
   Web of Science ®Google Scholar
• Mickaitytė A, Zavadskas EK, Kaklauskas A, Tupėnaitė L. 2008. The concept model of sustainable buildings refurbishment. Int J Strategic Property Manage. 12(1):53–68.
   Web of Science ®Google Scholar
• Negnevitsky M. 2011. Artificial intelligence: a guide to intelligent systems. 3rd ed. London: Pearson Education.
   Google Scholar
• Okakpu A, Ghaffarianhoseini A, Tookey J, Haar J, Ghaffarianhoseini A, Rehman AU. 2020. Risk factors that influence adoption of building information modelling (BIM) for refurbishment of complex building projects: stakeholders perceptions. Int J Constr Manage. 1–13. https://doi.org/10.1080/15623599.2020.1795985.
   Google Scholar
• Oses U, Rojí E, Cuadrado J, Larrauri M. 2018. Multiple-criteria decision-making tool for local governments to evaluate the global and local sustainability of transportation systems in urban areas: Case study. J Urban Plann Dev. 144(1):04017019.
   Web of Science ®Google Scholar
• Pedrycz W, Gomide F. 2007. Fuzzy systems engineering: toward human-centric computing. Hoboken (NJ): John Wiley & Sons, Inc.
   Google Scholar
• Saaty TL. 1980. The analytic hierarchy process. 1st ed. New York (NY): McGrow-Hill.
   Google Scholar
• Saaty TL. 1990. Decision making for leaders: the analytic hierarchy process for decisions in a complex world. 1st ed. Pittsburgh (PA): RWS Publications.
   Google Scholar
• Sargent RG. 2005. Verification and validation of simulation models. Paper presented at the 37th Conference on Winter Simulation.
   Google Scholar
• Sargent RG. 2011. Verification and validation of simulation models. Paper presented at the 2011 Winter Simulation Conference.
   Google Scholar
• Sarja A. 2002. Integrated life cycle design of structures. 1st ed. New York (NY): Spon Press.
   Google Scholar
• Schlesinger S, Crosbie RE, Gagne RE, Innis GS, Lalwani C, Loch J, Sylvester RJ, Wright RD, Kheir N, Bartos D. 1979. Terminology for model credibility. Simulation. 32(3):103–104.
   Google Scholar
• Sinou M, Kyvelou S. 2006. Present and future of building performance assessment tools. Manage Environ Quality. 17(5):570–586.
   Google Scholar
• Tzeng GH, Huang JJ. 2011. Multiple attribute decision making: methods and applications. Boca Raton (FL): CRC Press.
   Google Scholar
• Von Altrock C. 1995. Fuzzy logic and neurofuzzy applications explained. 1st ed. Hoboken (NJ): Prentice-Hall, Inc.
   Google Scholar
• Weerasinghe UGD. 2012. Development of a framework to assess sustainability of building projects [PhD thesis]. Calgary (Canada): University of Calgary.
   Google Scholar
• Wei C-C, Chien C-F, Wang M-JJ. 2005. An ahp-based approach to erp system selection. Int J Prod Econ. 96(1):47–62.
   Web of Science ®Google Scholar
• Yang J, Brandon PS, Sidwell AC. 2005. Smart and sustainable built environments. Oxford: Blackwell Publishing Ltd. https://onlinelibrary.wiley.com/doi/pdf/10.1002/9780470759493.
   Google Scholar
• Yen J, Langari R. 1999. Fuzzy logic: intelligence, control, and information. 1st ed. Hoboken, NJ: Prentice Hall.
   Google Scholar
• Yoon KP, Hwang C-L. 1995. Multiple attribute decision making: an introduction. 1st ed. Thousand Oaks, CA: Sage Publications, Inc.
   Google Scholar
• Yu J, Leung M-y, Jiang X. 2020. Impact of critical factors within decision making process of public engagement and public consultation for construction projects–case studies. Int J Constr Manage. 1–10. https://doi.org/10.1080/15623599.2020.1783600.
   Google Scholar
• Zahedi F. 1986. Analytic hierarchy process - a survey of the method and its applications. Interfaces. 16(4):96–108. 'The
   Web of Science ®Google Scholar
• Zhang G, Zou PXW. 2007. Fuzzy analytical hierarchy process risk assessment approach for joint venture construction projects in china. J Constr Eng Manage. 133(10):771–779.
   Web of Science ®Google Scholar
• Zolfani SH, Pourhossein M, Yazdani M, Zavadskas EK. 2018. Construction projects of hotels based on environmental sustainability with mcdm framework. Alexandria Eng J. 57(1):357–365. 'Evaluating
   Web of Science ®Google Scholar