English
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Decision support method for optimal modernization of residential buildings
DOI:
https://doi.org/10.24425/ace.2024.148908Abstract
Decision-making for the refurbishment of multi-family residential buildings is a complex and computationally difficult task. Therefore, the authors have developed a model that supports modernization planning in a long-term and comprehensive manner, i.e. from assessing the building to indicating the optimal scope of modernization. The comprehensive scope of the model includes the acquisition and provision of relevant knowledge to the model. The original methods proposed for its acquisition are derived from common expert knowledge based on linguistic terms. The methods adopted are not mandatory and may be replaced by others that provide more reliable knowledge. The fundamental aim of the proposed approach, however, is to select the optimal modernization option and allocate it over the planned modernization time horizon. An innovative optimisation approach based on decision matrices is used, allowing the selection of possible scenarios of repair options at each stage. These matrices are a set of constraints written in binary variables allowing the optimisation calculus to maintain a fixed sequence of repairs. In addition, the solutions used in the optimisation modules make it possible to take into account assumptions regarding the assumed assessment of the building’s condition and financial constraints. The developed model provides a practical and versatile tool that can be used by managers at the maintenance stage of residential buildings.References
[1] J.A. Dauda and S.O. Ajayi, “Understanding the impediments to sustainable structural retrofit of existing buildings in the UK”, Journal of Building Engineering, vol. 60, art. no. 105168, 2022, doi: 10.1016/j.jobe.2022.105168.
[2] R. Jagarajan, M.N. Abdullah Mohd Asmoni, A.H. Mohammed, M.N. Jaafar, J. Lee Yim Mei, and M. Baba, “Green retrofitting – A review of current status, implementations and challenges”, Renewable and Sustainable Energy Reviews, vol. 67, pp. 1360–1368, 2017, doi: 10.1016/j.rser.2016.09.091.
[3] P. Li and T.M. Froese, “A green home decision-making tool: Sustainability assessment for homeowners”, Energy and Buildings, vol. 150, pp. 421–431, 2017, doi: 10.1016/j.enbuild.2017.06.017.
[4] C. Jiménez-Pulido, A. Jiménez-Rivero, and J. García-Navarro, “Improved sustainability certification systems to respond to building renovation challenges based on a literature review”, Journal of Building Engineering, vol. 45, art. 103575, 2022, doi: 10.1016/j.jobe.2021.103575.
[5] L. D’Angelo, M. Hajdukiewicz, F. Seri, and M.M. Keane, “A novel BIM-based process workflow for building retrofit”, Journal of Building Engineering, vol. 50, art. no. 104163, 2022, doi: 10.1016/j.jobe.2022.104163.
[6] C. Nägeli, A. Farahani, M. Österbring, J-O. Dalenbäck, and H. Wallbaum, “A service-life cycle approach to maintenance and energy retrofit planning for building portfolios”, Building and Environment, vol. 160, art. no. 106212, 2019, doi: 10.1016/j.buildenv.2019.106212.
[7] F. Mostafazadeh, S.J. Eirdmousa, and M. Tavakolan, “Energy, economic and comfort optimization of building retrofits considering climate change: A simulation-based NSGA-III approach”, Energy and Buildings, vol. 280, art. no. 112721, 2023, doi: 10.1016/j.enbuild.2022.112721.
[8] E. Asadi, M. Gameiro da Silva, C.H. Antunes, and L. Dias, “A multi-objective optimization model for building retrofit strategies using TRNSYS simulations, GenOpt and MATLAB”, Building and Environment, vol. 56, pp. 370–378, 2012, doi: 10.1016/j.buildenv.2012.04.005.
[9] A. Hauashdh, J. Jailani, L.A. Rahman, and N. AL-fadhali, “Strategic approaches towards achieving sustainable and effective building maintenance practices in maintenance-managed buildings: A combination of expert interviews and a literature review”, Journal of Building Engineering, vol. 45, art. no. 103490, 2022, doi: 10.1016/j.jobe.2021.103490.
[10] Y. Xue, A. Temeljotov-Salaja, and C.M. Lindkvist, “Renovating the retrofit process: People-centered business models and co-created partnerships for low-energy buildings in Norway”, Energy Research & Social Science, vol. 85, art. no. 102406, 2022, doi: 10.1016/j.erss.2021.102406.
[11] A. Kamari, R. Corrao, and P.H. Kirkegaard, “Sustainability focused decision-making in building renovation”, International Journal of Sustainable Built Environment, vol. 6, no. 2, pp. 330–350, 2017, doi: 10.1016/j.ijsbe.2017.05.001.
[12] P.A. Jensen, E. Maslesa, J. Brinkø Berg, and Ch. Thuesen, “10 questions concerning sustainable building renovation”, Building and Environment, vol. 143, pp. 130–137, 2018, doi: 10.1016/j.buildenv.2018.06.051.
[13] R. Moschetti, H. Brattebø, K.S. Skeie, and A.G. Lien, “Performing quantitative analyses towards sustainable business models in building energy renovation projects: Analytic process and case study”, Journal of Cleaner Production, vol. 199, pp. 1092–1106, 2018, doi: 10.1016/j.jclepro.2018.06.091.
[14] D.X. Zhao, B.J. He, C. Johnson, and B. Mou, “Social problems of green buildings: From the humanistic needs to social acceptance”, Renewable and Sustainable Energy Reviews, vol. 51, pp. 1594–1609, 2015, doi: 10.1016/j.rser.2015.07.072.
[15] T.D. Mora, F. Peron, P. Romagnoni, M. Almeida, and M. Ferreira, “Tools and procedures to support decision making for cost-effective energy and carbon emissions optimization in building renovation”, Energy and Buildings, vol. 167, pp. 200–215, 2018, doi: 10.1016/j.enbuild.2018.02.030.
[16] M. Awada and I. Srour, “A genetic algorithm based framework to model the relationship between building renovation decisions and occupants’ satisfaction with indoor environmental quality”, Building and Environment, vol. 146, pp. 247–257, 2018, doi: 10.1016/j.buildenv.2018.10.001.
[17] A. Serrano-Jiméneza, M.L. Lima, M. Molina-Huelva, and Á. Barrios-Paduraa, “Promoting urban regeneration and aging in place: APRAM – An interdisciplinary method to support decision-making in building renovation”, Sustainable Cities and Society, vol. 47, art. no. 101505, 2019, doi: 10.1016/j.scs.2019.101505.
[18] Ch. Passoni, A. Marini, A. Belleri, and C. Menna, “Redefining the concept of sustainable renovation of buildings: State of the art and an LCT-based design framework”, Sustainable Cities and Society, vol. 64, art. no. 102519, 2021, doi: 10.1016/j.scs.2020.102519.
[19] F. Faqih and T. Zayed, “Defect-based building condition assessment”, Building and Environment, vol. 191, art. no. 107575, 2021, doi: 10.1016/j.buildenv.2020.107575.
[20] N. Kwon, Y. Ahn, B-S. Son, and H. Moon, “Developing a machine learning-based building repair time estimation model considering weight assigning methods”, Journal of Building Engineering, vol. 43, art. no. 102627, 2021, doi: 10.1016/j.jobe.2021.102627.
[21] A. Farahani, H. Wallbaum, and J-O. Dalenbäck, “The importance of life-cycle based planning in maintenance and Energy renovation of multifamily buildings”, Sustainable Cities and Society, vol. 44, pp. 715–725, 2019, doi: 10.1016/j.scs.2018.10.033.
[22] J. Choi and J. Kim, “Techno-economic feasibility study for deep renovation of old apartment”, Journal of Cleaner Production, vol. 382, art. no. 135396, 2023, doi: 10.1016/j.jclepro.2022.135396.
[23] R. Bucoń and A. Czarnigowska, “Sequential Model for Long-Term Planning of Building Renewal and Capital Improvement”, Sustainability, vol. 13, no. 17, art. no. 9575, 2021, doi: 10.3390/su13179575.
[24] R. Bucoń and A. Czarnigowska, “A model to support long-term building maintenance planning for multifamily housing”, Journal of Building Engineering, vol. 44, 2021, doi: 10.1016/j.jobe.2021.103000.
[25] J. Richarz, S. Henn, T. Osterhage, and D. Müller, “Optimal scheduling of modernization measures for typical non-residential buildings”, Energy, vol. 238, Part A, 2022, doi: 10.1016/j.energy.2021.121871.
[26] L. Junghans, “Sequential equi-marginal optimization method for ranking strategies for thermal building renovation”, Energy and Buildings, vol. 65, pp. 10–18, 2013, doi: 10.1016/j.enbuild.2013.05.028.
[27] K. Cho and T. Kim, “Optimized scheduling method for office building renovation projects”, Expert Systems with Applications, vol. 168, art. no. 114212, 2021, doi: 10.1016/j.eswa.2020.114212.
[28] M. AlOtaibi, K. El-Rayes, and A. Altuwaim, “Optimizing the Renovation Scheduling of Leased Residential Buildings to Minimize Total Project Cost”, Journal of Construction Engineering and Management, vol. 147, no. 7, 2021, doi: 10.1061/(ASCE)CO.1943-7862.0002063.
[29] Y. Cho, S. Lee, J. Lee, and J. Kim, “Analysis of the Repair Time of Finishing Works Using a Probabilistic Approach for Efficient Residential Buildings Maintenance Strategies”, Sustainability, vol. 13, no. 22, 2021, doi: 10.3390/su132212443.
[30] F-J. Shiue, M-C. Zheng, H-Y. Lee, A.F.K. Khitam, and P-Y. Li, “Renovation Construction Process Scheduling for Long-Term Performance of Buildings: An Application Case of University Campus”, Sustainability, vol. 11, no. 19, art. no. 5542, 2019, doi: 10.3390/su11195542.
[31] A. Farahani, H.Wallbaum, and J.-O. Dalenbäck, “Optimized maintenance and renovation scheduling in multifamily buildings – a systematic approach based on condition state and life cycle cost of building components”, Construction Management and Economics, vol. 37, no. 3, pp. 139–155, 2019, doi: 10.1080/01446193.2018.1512750.
[32] R. Matos, F. Rodrigues, H. Rodrigues, and A. Costa, “Building condition assessment supported by Building Information Modelling”, Journal of Building Engineering, vol. 38, art. no. 102186, 2021, doi: 10.1016/j.jobe.2021.102186.
[33] I. Petkov, G. Mavromatidis, Ch. Knoeri, J. Allan, and V.H. Hoffmann, “MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits”, Applied Energy, vol. 314, art. no. 118901, 2022, doi: 10.1016/j.apenergy.2022.118901.
[34] H. AL-Smadi, A. Al-Sakkaf, T. Zayed, and F. Nasiri, “An integrated space-based building maintenance management model using multi-objective optimization”, Smart and Sustainable Built Environment, vol. 12, no. 2, pp. 277–297, 2023, doi: 10.1108/SASBE-04-2021-0064.
[35] H. Son and Ch. Kim, “Evolutionary many-objective optimization for retrofit planning in public buildings: A comparative study”, Journal of Cleaner Production, vol. 190, pp. 403–410, 2018, doi: 10.1016/j.jclepro.2018.04.102.
[36] J.A.P. Amorocho and T. Hartmann, “A multi-criteria decision-making framework for residential building renovation using pairwise comparison and TOPSIS methods”, Journal of Building Engineering, vol. 53, art. no. 104596, 2022, doi: 10.1016/j.jobe.2022.104596.
[37] A. Serrano-Jiménez, P. Femenías, L. Thuvander, and A. Barrios-Padura, “A multi-criteria decision support method towards selecting feasible and sustainable housing renovation strategies”, Journal of Cleaner Production, vol. 278, art. no. 123588, 2021, doi: 10.1016/j.jclepro.2020.123588.
[38] J. Si and L. Marjanovic-Halburd, “Criteria weighting for green technology selection as part of retrofit decision making process for existing non-domestic buildings”, Sustainable Cities and Society, vol. 41, pp. 625–638, 2018, doi: 10.1016/j.scs.2018.05.051.
[39] D. Besiktepe, M.E. Ozbek, and R.A. Atadero, “Identification of the Criteria for Building Maintenance Decisions in Facility Management: First Step to Developing a Multi-Criteria Decision-Making Approach”, Buildings, vol. 10, no. 9, 2020, doi: 10.3390/buildings10090166.
[40] A. Kamari, P. H. Kirkegaard, C. Peter, and L. Schultz, “PARADIS – A process integrating tool for rapid generation and evaluation of holistic renovation scenarios”, Journal of Building Engineering, vol. 34, art. no. 101944, 2021, doi: 10.1016/j.jobe.2020.101944.
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