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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Akinade, O. O.
Languages: English
Types: Doctoral thesis
Subjects:
The Construction industry generates about 30% of the total waste in the UK. Current high landfill cost and severe environmental impact of waste reveals the need to reduce waste generated from construction activities. Although literature reveals that the best approach to Construction Waste (CW) management is minimization at the design stage, current tools are not robust enough to support architects and design engineers. Review of extant literature reveals that the key limitations of existing CW management tools are that they are not integrated with the design process and that they lack Building Information Modelling (BIM) compliance. This is because the tools are external to design BIM tools used by architects and design engineers. This study therefore investigates BIM-based strategies for CW management and develops Artificial Intelligent (AI) hybrid models to predict CW at the design stage. The model was then integrated into Autodesk Revit as an add-in (BIMWaste) to provide CW analytics. \ud \ud Based on a critical realism paradigm, the study adopts exploratory sequential mixed methods, which combines both qualitative and quantitative methods into a single study. The study starts with the review of extant literature and (FGIs) with industry practitioners. The transcripts of the FGIs were subjected to thematic analysis to identify prevalent themes from the quotations. The factors from literature review and FGIs were then combined and put together in a questionnaire survey and distributed to industry practitioners. The questionnaire responses were subjected to rigorous statistical process to identify key strategies for BIM-based approach to waste efficient design coordination. \ud \ud Results of factor analysis revealed five groups of BIM strategies for CW management, which are: (i) improved collaboration for waste management, (ii) waste-driven design process and solutions, (iii) lifecycle waste analytics, (iv) Innovative technologies for waste intelligence and analytics, and (v) improved documentation for waste management. The results improve the understanding of BIM functionalities and how they could improve the effectiveness of existing CW management tools. Thereafter, the key strategies were developed into a holistic BIM framework for CW management. This was done to incorporate industrial and technological requirements for BIM enabled waste management into an integrated system.\ud \ud The framework guided the development of AI hybrid models and BIM based tool for CW management. Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed for CW prediction and mathematical models were developed for CW minimisation. Based on historical Construction Waste Record (CWR) from 117 building projects, the model development reveals that two key predictors of CW are “GFA” and “Construction Type”. The final models were then incorporated into Autodesk Revit to enable the prediction of CW from building designs. The performance of the final tool was tested using a test plan and two test cases. The results show that the tool performs well and that it predicts CW according to waste types, element types, and building levels. The study generated several implications that would be of interest to several stakeholders in the construction industry. Particularly, the study provides a clear direction on how CW management strategies could be integrated into BIM platform to streamline the CW analytics.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1) Olugbenga O. Akinade, Lukumon O. Oyedele, Kamil Omoteso, Saheed O. Ajayi, Muhammad Bilal, Hakeem A. Owolabi, Hafiz A. Alaka, Lara Ayris, John Henry Looney, BIM-based deconstruction tool: Towards essential functionalities, International Journal of Sustainable Built Environment, Available online 29 January 2017
    • 2) Akinade, O.O., Oyedele, L.O., Ajayi, S.O., Bilal, M., Alaka, H.A., Owolabi, H.A., Bello, S.A., Jaiyeoba, B.E. and Kadiri, K.O., 2016. Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills. Waste Management.
    • 3) Akinade, O.O., Oyedele, L.O., Munir, K., Bilal, M., Ajayi, S.O., Owolabi, H.A., Alaka, H.A. and Bello, S.A., 2016. Evaluation criteria for construction waste management tools: towards a holistic BIM framework. International Journal of Sustainable Building Technology and Urban Development, pp. 1-19.
    • 4) Akinade, O.O., Oyedele, L.O., Bilal, M., Ajayi, S.O., Owolabi, H.A., Alaka, H.A. and Bello, S.A., 2015. Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS). Resources, Conservation and Recycling, 105, pp. 167-176.
    • 5) Bilal, M., Oyedele, L.O., Munir, K., Ajayi, S.O., Akinade, O.O., Owolabi, H.A. and Alaka, H.A., 2017. The application of web of data technologies in building materials information modelling for construction waste analytics. Sustainable Materials and Technologies.
    • 6) Bilal, M., Oyedele, L.O., Qadir, J., Munir, K., Ajayi, S.O., Akinade, O.O., Owolabi, H.A., Alaka, H.A. and Pasha, M., 2016. Big Data in the construction industry: A review of present status, opportunities, and future trends. Advanced Engineering Informatics, 30(3), pp. 500-521.
    • 7) Bilal, M., Oyedele, L.O., Akinade, O.O., Ajayi, S.O., Alaka, H.A., Owolabi, H.A., Qadir, J., Pasha, M. and Bello, S.A., 2016. Big data architecture for construction waste analytics (CWA): A conceptual framework. Journal of Building Engineering, 6, pp. 144-156.
    • 8) Bilal, M., Oyedele, L.O., Qadir, J., Munir, K., Akinade, O.O., Ajayi, S.O., Alaka, H.A. and Owolabi, H.A., 2015. Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data. International vii
    • Lee, J.K. (2011) Building Environment Rule and Analysis (BERA) Language. (no place) PhD Thesis: Georgia Institute of Technology.
    • Lee, S.-K., Kim, K.-R. and Yu, J.-H. (2014) BIM and ontology-based approach for building cost estimation. Automation in construction. 41 pp. 96-105.
    • Lenfle, S. (2014) Toward a genealogy of project management: Sidewinder and the management of exploratory projects. International Journal of Project Management. 32 (6), pp. 921-931. doi:10.1016/j.ijproman.2013.10.017.
    • Li, H., Chen, Z., Yong, L. and Kong, S.C.W. (2005) Application of integrated GPS and GIS technology for reducing construction waste and improving construction efficiency. Automation in Construction. 14 (3), pp. 323-331. doi:10.1016/j.autcon.2004.08.007.
    • Li, H.M. and Wang, Z.F. (2009) Applying self-adaptive ant colony optimization for construction time-cost optimization. In: 2009 International Conference on Management Science and Engineering - 16th Annual Conference Proceedings, ICMSE 2009. 2009 pp. 283-289. doi:10.1109/ICMSE.2009.5317463.
    • Li, J., Ding, Z., Mi, X. and Wang, J. (2013) A model for estimating construction waste generation index for building project in China. Resources, Conservation and Recycling. 74 pp. 20-26. doi:10.1016/j.resconrec.2013.02.015.
    • Li, Y. and Zhang, X. (2013) Web-based construction waste estimation system for building construction projects. Automation in Construction. 35 (1), pp. 142-156. doi:10.1016/j.autcon.2013.05.002.
    • Liang, T. (1987) User interface design for decision support systems: A self-adaptive approach. Information & Management [online]. 12 (4), pp. 181-193. Available from: http://www.sciencedirect.com/science/article/pii/0378720687900413doi:10.1016/0378- 7206(87)90041-3 [Accessed 10 January 2015].
    • Lichtig, W.A. (2010) The Integrated Agreement for Lean Project Delivery. In: Improving Healthcare through Built Environment Infrastructure. pp. 85-101. doi:10.1002/9781444319675.ch6.
    • Lindstrom, L. and Jeffries, R. (2004) Extreme Programming and Agile Software Development Methodologies. Information Systems Management [online]. 21 (3), pp. 41-52. Available from: http://www.tandfonline.com/doi/pdf/10.1201/1078/44432.21.3.20040601/82476.7%5Cnhttp ://www.tandfonline.com/doi/abs/10.1201/1078/44432.21.3.20040601/82476.7doi:10.1201/1 078/44432.21.3.20040601/82476.7.
    • Liu, T. and Wilkinson, S. (2014) Large-scale public venue development and the application of Public-Private Partnerships (PPPs). International Journal of Project Management. 32 (1), pp. 88-100. doi:10.1016/j.ijproman.2013.01.003.
    • Liu, Z., Osmani, M., Demian, P. and Baldwin, A. (2011) The potential use of BIM to aid construction waste minimalisation. In: Proceedings of the CIB W78-W102 2011: International Conference. 2011 Sophia Antipolis, France: .
    • Livermore, J. (2007) Factors that impact implementing an agile software development methodology. Proceedings 2007 IEEE SoutheastCon [online]. pp. 82-86. Available from: http://apps.webofknowledge.com.db.ub.oru.se/full_record.do?product=WOS&search_mode =GeneralSearch&qid=3&SID=P2awwaI4gR5EcT2yRvu&page=6&doc=56doi:10.1109/SE CON.2007.342860.
    • Llatas, C. (2011) A model for quantifying construction waste in projects according to the European waste list. Waste management (New York, N.Y.). 31 (6), pp. 1261-1276. doi:10.1016/j.wasman.2011.01.023.
    • Long, T., Yoon, I., Porter, A., Sussman, A. and Memon, A. (2012) Overlap and Synergy in Testing Software Components across Loosely Coupled Communities. In: Software Reliability Engineering (ISSRE), 2012 IEEE 23rd International Symposium on. 2012 (no place) IEEE. pp. 171-180.
    • Lopez, R. and Love, P.E.D. (2012) Design Error Costs in Construction Projects Journal of Construction Engineering and Management 138 p.pp. 585-593. doi:10.1061/(ASCE)CO.1943-7862.0000454.
    • Lu, W., Yuan, H., Li, J., Hao, J.J.L., Mi, X. and Ding, Z. (2011) An empirical investigation of construction and demolition waste generation rates in Shenzhen city, South China. Waste management. 31 (4), pp. 680-687.
    • MacLeamy, P. (2004) MacLeamy Curve. Collaboration, Integrated Information, and the Project Lifecycle in Building Design and Construction and Operation (WP-1202).
    • Magnaye, R., Sauser, B., Patanakul, P., Nowicki, D. and Randall, W. (2014) Earned readiness 262
    • Maier, E.R. and Branzei, O. (2014) 'On time and on budget': Harnessing creativity in large scale projects. International Journal of Project Management. 32 (7), pp. 1123-1133. doi:10.1016/j.ijproman.2014.02.009.
    • Maliene, V., Grigonis, V., Palevičius, V. and Griffiths, S. (2011) Geographic information system: Old principles with new capabilities. Urban Design International. 16 (1), pp. 1-6.
    • Manning, R. and Messner, J. (2008) Case studies in BIM implementation for programming of healthcare facilities. In: ITcon - IT in Construction, 13 (Special Issue - Case studies of BIM use). 2008 (no place) ITcon.
    • Masudi, A.F., Rosmani, C., Hassan, C., Mahmood, N.Z. and Mokhtar, S.N. (2011) Construction Waste Quantification and Benchmarking : A Study in Klang Valley , Malaysia. 5 pp. 909- 916.
    • Matsueda, N. and Nagase, Y. (2012) An economic analysis of the packaging waste recovery note system in the UK. Resource and Energy Economics. 34 (4), pp. 669-679.
    • Mazairac, W. and Beetz, J. (2013) BIMQL-An open query language for building information models. Advanced Engineering Informatics. 27 (4), pp. 444-456.
    • Mcdonald, B. and Smithers, M. (1998) Implementing a waste management plan during the construction phase of a project: a case study. Construction Management and Economics. 16 (1), pp. 71-78. doi:10.1080/014461998372600.
    • McDonough, W. and Braungart, M. (2002) Remaking the way we make things: Cradle to cradle. New York: North Point Press.
    • Mcgrath, C. (2001) Waste minimisation in practice. Resources, Conservation and Recycling. 32 (1), pp. 227-238.
    • McKechnie, E. and Brown, E. (2007) Achieving effective waste minimisation through design. Waste & Resources Action Programme (WRAP), Oxen.
    • Melin, P., Castillo, O., Kacprzyk, J. and Pedrycz, W. (2007) Design of Hybrid Intelligent Systems [online].
    • Mihic, M., Sertic, J. and Zavrski, I. (2014) Integrated Project Delivery as Integration between Solution Development and Solution Implementation. Procedia - Social and Behavioral Sciences [online]. 119 pp. 557-565. Available from: http://www.sciencedirect.com/science/article/pii/S1877042814021533doi:10.1016/j.sbspro.
    • Mills, T.H., Showalter, E. and Jarman, D. (1999) A cost effective waste management plan. Cost Engineering. 41 (3), pp. 35-43.
    • Minsky, N. (1975) A framework for representing knowledge in the psychology of computer vision (Winston O., ed) McGraw-Hill. New York.
    • Mohanty, R., Ravi, V. and Patra, M.R. (2013) Hybrid intelligent systems for predicting software reliability. Applied Soft Computing Journal. 13 (1), pp. 189-200. doi:10.1016/j.asoc.2012.08.015.
    • Mokhtar, S.N., Mahmood, N.Z., Che Hassan, C.R., Masudi, A.F. and Sulaiman, N.M. (2011) Factors that contribute to the generation of construction waste at sites. Advanced Materials Research. 163 pp. 4501-4507.
    • Morgan, D.L. (2007) Paradigms Lost and Pragmatism Regained: Methodological Implications of Combining Qualitative and Quantitative Methods. Journal of Mixed Methods Research. 1 (1), pp. 48-76. doi:10.1177/2345678906292462.
    • Morrissey, a J. and Browne, J. (2004) Waste management models and their application to sustainable waste management. Waste management (New York, N.Y.). 24 (3), pp. 297-308. doi:10.1016/j.wasman.2003.09.005.
    • Mosa, A.M., Taha, M.R., Ismail, A. and Rahmat, R.A.O.K. (2013) A diagnostic expert system to overcome construction problems in rigid highway pavement. Journal of Civil Engineering and Management. 19 (6), pp. 846-861.
    • Moustakas, C. (1994) Phenomenological research methods. (no place) Sage Publications.
    • Munakata, T., Jani, Y. and Engineering, S. (1994) Fuzzy systems: An overview. Communications of the ACM [online]. 37 (3), pp. 69-77. Available from: http://doc.utwente.nl/72926/1/Top91qualitative.pdf.
    • Musca, G.N., Mellet, C., Simoni, G., Sitri, F. and de Vogüé, S. (2014) 'Drop your boat!': The discursive co-construction of project renewal. The case of the Darwin mountaineering expedition in Patagonia. International Journal of Project Management. 32 (7), pp. 1157- 1169. doi:10.1016/j.ijproman.2014.02.006.
    • Nagapan, S., Rahman, I.A., Asmi, A., Hameed, A. and Zin, R.M. (2012a) Identifying Causes of Construction Waste - Case of Central Region of Peninsula Malaysia. International Journal of Integrated Engineering, Vol. 4 No. 2 (2012) p. 22-28. 4 (2), pp. 22-28.
    • Nagapan, S., Rahman, I.A., Asmi, A., Memon, A.H. and Latif, I. (2012b) Issues on Construction Waste : The Need for Sustainable Waste Management. (Chuser), pp. 329-334.
    • Nepal, M.P., Staub-French, S., Pottinger, R. and Webster, A. (2012) Querying a building information model for construction-specific spatial information. In: Advanced Engineering Informatics. 2012 pp. 904-923. doi:10.1016/j.aei.2012.08.003.
    • Nepal, M.P., Zhang, J., Webster, A., Staub-French, S., Pottinger, R. and Lawrence, M. (2009) Querying IFC-based building information models to support construction management functions. Proceeding of the 2009 Construction Research Congress [online]. pp. 506-515. Available from: http://ascelibrary.org/doi/abs/10.1061/41020(339)52doi:10.1061/41020(339)52.
    • Nerur, S., Mahapatra, R. and Mangalaraj, G. (2005) Challenges of Migrating to Agile Methodologies. Communications of the ACM. 48 (2), pp. 72-78. doi:10.1145/1060710.1060712.
    • Neuman, W.L. (2009) Social Research Methods: Qualitative and Qualitative approaches. Boston: Allyn and Bacon.
    • O'Cathain, A., Murphy, E. and Nicholl, J. (2007) Why, and how, mixed methods research is undertaken in health services research in England: a mixed methods study. BMC health services research. 7 (1), pp. 85. doi:10.1186/1472-6963-7-85.
    • Omkar, S.N., Senthilnath, J., Khandelwal, R., Naik, G.N. and Gopalakrishnan, S. (2011) Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures. Applied Soft Computing. 11 (1), pp. 489-499.
    • Onwuegbuzie, A.J. and Leech, N.L. (2005) On Becoming a Pragmatic Researcher: The Importance of Combining Quantitative and Qualitative Research Methodologies. International Journal of Social Research Methodology. 8 (5), pp. 375-387. doi:10.1080/13645570500402447.
    • Ortiz, O., Castells, F. and Sonnemann, G. (2009) Sustainability in the construction industry: A review of recent developments based on LCA. Construction and Building Materials [online]. 23 (1), pp. 28-39. Available from: http://www.sciencedirect.com/science/article/pii/S0950061807003005doi:10.1016/j.conbuil dmat.2007.11.012 [Accessed 14 July 2014].
    • Osmani, M. (2011) Construction waste. Waste: A Handbook for Management, Elsevier. pp. 207- 218.
    • Osmani, M. (2012a) Construction waste minimization in the UK: current pressures for change and approaches. Procedia - Social and Behavioral Sciences. 40 pp. 37-40.
    • Osmani, M. (2012b) Construction Waste Minimization in the UK: Current Pressures for Change and Approaches. Procedia - Social and Behavioral Sciences. 40 pp. 37-40. doi:10.1016/j.sbspro.2012.03.158.
    • Osmani, M. (2013) Design waste mapping: a project life cycle approach. Proceedings of the ICEWaste and Resource Management. 166 (3), pp. 114-127.
    • Osmani, M., Glass, J. and Price, A.D.F. (2008) Architects' perspectives on construction waste reduction by design. Waste Management. 28 (7), pp. 1147-1158.
    • Otto, M. (1990) Fuzzy expert systems [online].
    • Oyedele, L.O. (2013) Analysis of architects' demotivating factors in design firms. International Journal of Project Management [online]. 31 (3), pp. 342-354. Available from: http://dx.doi.org/10.1016/j.ijproman.2012.11.009doi:10.1016/j.ijproman.2012.11.009 [Accessed 25 October 2015].
    • Oyedele, L.O., Ajayi, S.O. and Kadiri, K.O. (2014) Use of recycled products in UK construction industry: An empirical investigation into critical impediments and strategies for improvement. Resources, Conservation and Recycling [online]. 93 pp. 23-31. Available from: http://www.sciencedirect.com/science/article/pii/S0921344914002018doi:10.1016/j.resconr ec.2014.09.011 [Accessed 20 November 2015].
    • Oyedele, L.O., Regan, M., von Meding, J., Ahmed, A., Ebohon, O.J. and Elnokaly, A. (2013) Reducing waste to landfill in the UK: identifying impediments and critical solutions. World Journal of Science, Technology and Sustainable Development. 10 (2), pp. 131-142.
    • Oyedele, L.O. and Tham, K.W. (2007) Clients' assessment of architects' performance in building delivery process: Evidence from Nigeria. Building and Environment [online]. 42 (5), pp. 2090-2099. Available from: http://www.sciencedirect.com/science/article/pii/S0360132306001107doi:10.1016/j.builden v.2005.06.030 [Accessed 15 March 2016].
    • Parnas, D.L. and Clements, P.C. (1986) A Rational Design Process: How And Why To Fake It Transactions on Software Engineering 12 (2) p.pp. 251-257. doi:10.1007/3-540-15199-0_6.
    • Pasquire, C.. and Gibb, A.G.F. (2002) Considerations for assessing the benefits of standardisation and pre- assembly in construction. Journal of Financial Management of Property and Construction. Vol. 7 pp. 151-161.
    • Patton, M.Q. (1997) Utilisation-focused evaluation: the new century text. Utilisation-focused evaluation: the new century text.
    • Pazlar, T. and Turk, Ž. (2008) Interoperability in practice: Geometric data exchange using the IFC standard. Electronic Journal of Information Technology in Construction. 13 pp. 362-380.
    • Petroutsatou, K., Georgopoulos, E., Lambropoulos, S. and Pantouvakis, J.P. (2011) Early cost estimating of road tunnel construction using neural networks. Journal of construction Phillips, P.S., Tudor, T., Bird, H. and Bates, M. (2011) A critical review of a key waste strategy initiative in England: Zero waste places projects 2008-2009. Resources, Conservation and Recycling. 55 (3), pp. 335-343.
    • Polkinghorne, D.E. (1989) Phenomenological research methods. In: Existential-phenomenological perspectives in psychology. (no place) Springer. pp. 41-60.
    • Pollack, J. (2007) The changing paradigms of project management. International Journal of Project Management. 25 (3), pp. 266-274.
    • Poon, C.S. (2007) Reducing construction waste. Waste management (New York, N.Y.) [online]. 27 (12), pp. 1715-1716. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17904489doi:10.1016/j.wasman.2007.08.013 [Accessed 29 December 2014].
    • Poon, C.S., Yu, A.T.W. and Jaillon, L. (2004) Reducing building waste at construction sites in Hong Kong. Construction Management and Economics. 22 (5), pp. 461-470. doi:10.1080/0144619042000202816.
    • Poon, C.S., Yu, A.T.W., Wong, S.W. and Cheung, E. (2004) Management of construction waste in public housing projects in Hong Kong. Construction Management & Economics. 22 (7), pp. 675-689.
    • Porwal, A. and Hewage, K.N. (2013) Building Information Modeling (BIM) partnering framework for public construction projects. Automation in Construction. 31 pp. 204-214. doi:10.1016/j.autcon.2012.12.004.
    • Qian, G., Wang, H. and Feng, X. (2013) Generalized hesitant fuzzy sets and their application in decision support system. Knowledge-Based Systems [online]. 37 pp. 357-365. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0950705112002390doi:10.1016/j.knosys.2012.0 8.019 [Accessed 10 January 2015].
    • RIBA (2016) National BIM Report 2016. Available from: https://www.thenbs.com/- /media/uk/files/pdf/bim-report-2016.pdf?la=en [Accessed 23 October 2016].
    • Royce, W.W. (1970) Managing the Development of Large Software Systems. Proceedings of IEEE WESCON [online]. 26 (8), pp. 328-338. Available from: http://leadinganswers.typepad.com/leading_answers/files/original_waterfall_paper_winston _royce.pdf.
    • Russell, S.J. and Norvig, P. (2010) Artificial Intelligence: A Modern Approach [online].
    • Sacks, R., Eastman, C.M. and Lee, G. (2004) Parametric 3D modeling in building construction with examples from precast concrete. Automation in Construction. 13 (3), pp. 291-312.
    • Sacks, R., Radosavljevic, M. and Barak, R. (2010) Requirements for building information modeling based lean production management systems for construction. Automation in Construction. 19 (5), pp. 641-655. doi:10.1016/j.autcon.2010.02.010.
    • Sage, D., Dainty, A. and Brookes, N. (2014) A critical argument in favor of theoretical pluralism: Project failure and the many and varied limitations of project management. International Journal of Project Management. 32 (4), pp. 544-555. doi:10.1016/j.ijproman.2013.08.005.
    • Sahota, P.S. and Jeffrey, P. (2005) Decision-support tools : moving beyond a technical orientation. Proceedings of the ICE-Engineering Sustainability,. 158 (3), pp. 127-134.
    • Salem, O., Asce, M., Shahin, A. and Khalifa, Y. (2008) Minimizing Cutting Wastes of Reinforcement Steel Bars Using Genetic Algorithms and Integer Programming Models. 133 (12), pp. 982-992.
    • Sandelowski, M. (2000) Focus on Research Methods Combining Qualitative and Quantitative Sampling , Data Collection , and Analysis Techniques in Mixed-Method Studies. 23 (3), pp. 246-255.
    • Sawhney, A. and Maheswari, J.U. (2013) Design Coordination Using Cloud-based Smart Building Element Models. International Journal of Computer Information Systems and Industrial Management Applications. 5 pp. 445-453.
    • Serpell, A. and Labra, M. (2003) A study on construction waste in Chile. In: George Ofori and Florence Yean Yng Ling (eds.). Proceedings, Joint Symposium of CIB W55, W65 and W107 on Knowledge Construction. 2003 pp. 102-111.
    • Shadish, W.R., Cook, T.D. and Leviton, L.C. (1991) Foundations of program evaluation: Theories of practice. (no place) Sage.
    • Shen, L.-Y., Lu, W.-S., Yao, H. and Wu, D.-H. (2005) A computer-based scoring method for measuring the environmental performance of construction activities. Automation in Construction. 14 (3), pp. 297-309. doi:10.1016/j.autcon.2004.08.017.
    • Shenhar, A.J. and Dvir, D. (1996) Toward a typological theory of project management. Research Policy [online]. 25 (4), pp. 607-632. Available from: http://linkinghub.elsevier.com/retrieve/pii/0048733395008772doi:10.1016/0048- 7333(95)00877-2 [Accessed 25 April 2017].
    • Sii, H.S., Ruxton, T. and Wang, J. (2002) Synthesis using fuzzy set theory and a DempsterShafer-based approach to compromise decision-making with multiple-attributes applied to risk control options selection. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 216 (1), pp. 15-29.
    • Solís-Guzmán, J., Marrero, M., Montes-Delgado, M.V. and Ramírez-de-Arellano, A. (2009) A Spanish model for quantification and management of construction waste. Waste Management. 29 (9), pp. 2542-2548. doi:http://dx.doi.org/10.1016/j.wasman.2009.05.009.
    • Tashakkori, a. and Creswell, J.W. (2007) Editorial: The New Era of Mixed Methods. Journal of Mixed Methods Research. 1 (1), pp. 3-7. doi:10.1177/2345678906293042.
    • Teo, M.M.M. and Loosemore, M. (2001) A theory of waste behaviour in the construction industry. Construction Management and Economics. 19 (7), pp. 741-751. doi:10.1080/01446190110067037.
    • Thomas, D. (2005) Agile programming: Design to accommodate Change. IEEE Software. 22 (3), pp. 14-16. doi:10.1109/MS.2005.54.
    • Thormark, C. (2001) Assessing the recycling potential in buildings. In: CIB Task Group 39: Deconstruction and Materials Reuse: Technology, Economic, and Policy. 2001 (no place) University of Florida. pp. 78-86.
    • Tibaut, A., Rebolj, D. and Perc, M.N. (2014) Interoperability requirements for automated manufacturing systems in construction. Journal of Intelligent Manufacturing. pp. 1-12.
    • Tingley, D.D. (2012) Design for Deconstruction: An Appraisal. (no place) PhD thesis, The University of Sheffield.
    • Tolman, F.P. (1999) Product modeling standards for the building and construction industry: past, present and future. Automation in construction. 8 (3), pp. 227-235.
    • Treloar, G.J., Gupta, H., Love, P.E.D. and Nguyen, B. (2003) An analysis of factors influencing waste minimisation and use of recycled materials for the construction of residential buildings. Management of Environmental Quality: An International Journal. 14 (1), pp. 134-145.
    • Trikha, D.N. (1999) Industrialised building systems: Prospects in Malaysia. In: Proceedings World Engineering Congress. 1999 Malaysia: .
    • Turban, E. and Aronson, J. (2005) Decision Support Systems and Intelligent Systems [online]. 7th edition. (no place) Pearson Prentice Hall.
    • Turk, D., France, R. and Rumpe, B. (2002) Limitations of agile software processes. In: Third International Conference on eXtreme Programming and Agile Processes in Software Engineering. 2002 pp. 43-46.
    • Vernikos, V.K., Goodier, C.I., Gibb, a G.F., Robery, P.C. and Broyd, T.W. (2012) Realising offsite construction and standardisation within a leading UK infrastructure consultancy. pp. 1-10.
    • Walford, G. (2010) Site Selection within Comparative Case Study and Ethnographic Research. Compare: A Journal of Comparative and International Education. 31 (2), pp. 151-164. doi:10.1080/03057920120068485.
    • Wang, J.-Y., Kang, X.-P. and Tam, V.W.-Y. (2008) An investigation of construction wastes: an empirical study in Shenzhen. Journal of Engineering, Design and Technology [online]. 6 pp. 227-236. Available from: http://ezproxy.itcr.ac.cr:2084/doi/pdfplus/10.1108/17260530810918252doi:10.1108/172605 30810918252.
    • Wang, J., Li, Z. and Tam, V.W.Y. (2014) Critical factors in effective construction waste minimization at the design stage: A Shenzhen case study, China. Resources, Conservation and Recycling. 82 pp. 1-7. doi:10.1016/j.resconrec.2013.11.003.
    • Wang, J.Y., Touran, A., Christoforou, C. and Fadlalla, H. (2004) A systems analysis tool for construction and demolition wastes management. Waste management (New York, N.Y.). 24 (10), pp. 989-997. doi:10.1016/j.wasman.2004.07.010.
    • Wang, X. and Chong, H. (2014) The Challenges and Trends of Building Information Modelling ( BIM ) for Construction and Resources Sectors. (Isarc), .
    • Webster, M.D. and Costello, D. (2005) Designing structural systems for deconstruction: How to extend a new building's useful life and prevent it from going to waste when the end finally comes. In: Greenbuild Conference, Atlanta, GA. 2005
    • Weise, M., Katranuschkov, P. and Scherer, R.J. (2003) Generalised Model Subset Definition Schema. In: Proc. CIB-W78 Conf. 2003 - Information Technology for Construction [online]. 2003 Available from: https://www.cs.auckland.ac.nz/w78/papers/ [Accessed 23 October 2014].
    • Wilmot, C.G. and Mei, B. (2005) Neural network modeling of highway construction costs. Journal of construction engineering and management. 131 (7), pp. 765-771.
    • Winch, G.M. (2014) Three domains of project organising. International Journal of Project Management. 32 (5), pp. 721-731. doi:10.1016/j.ijproman.2013.10.012.
    • Won, J., Cheng, J.C.P. and Lee, G. (2016) Quantification of construction waste prevented by BIMbased design validation: Case studies in South Korea. Waste management (New York, N.Y.) [online]. Available from: http://www.sciencedirect.com/science/article/pii/S0956053X15302592doi:10.1016/j.wasma n.2015.12.026 [Accessed 16 February 2016].
    • Wright, J.A., Loosemore, H.A. and Farmani, R. (2002) Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and buildings. 34 (9), pp. 959-972.
    • Wu, Z., Fan, H. and Liu, G. (2013) Forecasting Construction and Demolition Waste Using Gene Expression Programming. Journal of Computing in Civil Engineering. pp. 4014059. doi:10.1061/(ASCE)CP.1943-5487.0000362.
    • Wu, Z., Yu, A.T.W., Shen, L. and Liu, G. (2014) Quantifying construction and demolition waste: an analytical review. Waste management (New York, N.Y.). 34 (9), pp. 1683-1692. doi:10.1016/j.wasman.2014.05.010.
    • Xu, X., Ding, L., Luo, H. and Ma, L. (2014) From building information modeling to city information modeling. Journal of Information Technology in Construction, Special Issue BIM Cloud-based Technology in the AEC Sector: Present Status and Future Trends. 19 pp. 292- 307.
    • Yang, L.-R., Huang, C.-F. and Hsu, T.-J. (2014) Knowledge leadership to improve project and organizational performance. International Journal of Project Management. 32 (1), pp. 40- 53. doi:10.1016/j.ijproman.2013.01.011.
    • Yu, N., Jiang, Y., Luo, L., Lee, S., Jallow, A., Wu, D., Messner, J.I., Leicht, R.M. and Yen, J. (2013) Integrating BIMserver and OpenStudio for energy efficient building. In: Proceedings of 2013 ASCE International Workshop on Computing in Civil Engineering. 2013
    • Yu, W. and Skibniewski, M.J. (2009) Integrating neurofuzzy system with conceptual cost estimation to discover cost-related knowledge from residential construction projects. Journal of Computing in Civil Engineering. 24 (1), pp. 35-44.
    • Yu, W.D. and Skibniewski, M.J. (1999) Quantitative constructability analysis with a neuro-fuzzy knowledge-based multi-criterion decision support system. Automation in construction. 8 (5), pp. 553-565. doi:10.1016/S0926-5805(98)00105-8.
    • Yuan, H. (2012) A model for evaluating the social performance of construction waste management. Waste management. 32 (6), pp. 1218-1228.
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