References:

H. Abaza. An interactive design advisor for energy efficient building, Journal of Green Building, 3 (1) (2008), pp. 112-125

M. Abdallah, K. El-rayes. Optimizing the selection of building upgrade measures to minimize the operational negative environmental impacts of existing buildings, Building and Environment, 84 (2015), pp. 32-43

AIA, The American Institute of Architects (2007). Integrated Project Delivery: A Guide, ver. 1. Retrieved 1, 9, 2017, from 〈http://www.aia.org/ipdg〉.

Ü. Alev, L. Eskola, E. Arumägi, J. Jokisalo. Renovation alternatives to improve energy performance of historic rural houses in the baltic sea region, Energy and Buildings, 77 (2014), pp. 58-66

O. Alshamrani, K. Galal, S. Alkass. Integrated LCA-LEED sustainability assessment model for structureand envelope systems of school buildings, Building and Environment, 80 (2014), pp. 61-70

C. Anand, B. Amor. Recent developments, future challenges and new research directions in LCA of buildings: A critical review, renewable and Sustainable Energy Reviews, 67 (2017), pp. 408-416

E. Asadi, M.G. Silva, C.H. da, Antunes, L. Dias, L. Glicksman. Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application, Energy and Buildings, 81, Elsevier (2014), pp. 444-456

F. Ascione, N. Bianco, C. De Stasio, G.M. Mauro, G.P. Vanoli. CASA, cost-optimal analysis by multi-objective optimisation and artificial neural networks: A new framework for the robust assessment of cost-optimal energy retrofit, feasible for any building, 146, Energy and Buildings, Elsevier B.V (2017), pp. 200-219

F. Asdrubali, C. Baldassarri, V. Fthenakis. Life Cycle Analysis in the construction sector: Guiding the optimization of conventional Italian buildings, Energy and Buildings, 64 (2013), pp. 73-8

ASHRAE Design Guide. Advanced energy design guide for small to medium office buildings.
Book. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc, Atlanta (2014)

Athena Impact Estimator. (2017, 10 14). Athena Impact Estimator for Buildings V4.2 Software and Database Overview. Retrieved 10, 14, 2017, from 〈https://calculatelca.com/software/impact-estimator/user-manual/〉

N.M. Bouchlaghem, K.M. Letherman. Numerical optimization applied to the thermal design of buildings,Build Environ, 25 (2) (1990), pp. 117-124

A. Bolattürk. Optimum insulation thicknesses for building walls with respect to cooling and heating degree-hours in the warmest zone of Turkey, Building and Environment, 43 (2008), pp. 1055-1064

M. Bowick, J. O’Connor, J. Meil, Athena Guide to Whole-Building LCA in Green Building Programs (2014), pp. 1-41

J. Branke, K. Deb, K. Miettinen (Eds.), Multiobjective optimization: Interactive and evolutionary approaches, Vol. 5252, Springer Science & Business Media (2008)

M. Buyle, J. Braet, A. Audenaert. Life cycle assessment in the construction sector: A review, Renewable & Sustainable Energy Reviews, 26 (2013), pp. 379-388

L. Cabeza, L. Rincón, i Vilariño, G. Pérez, A. Castell. Life Cycle Assessment (LCA) and Life Cycle Energy Analysis (LCEA) of buildings and the building sector: A review, Renewable and Sustainable Energy Reviews, 29 (2014), pp. 394-416

CaGBC the Canadian Green Building Council (CaGBC). Retrieved 2, 14, 2017, from〈https://www.cagbc.org/〉.

F.P. Chantrelle, H. Lahmidi, W. Keilholz, M. Mankibi, El, P. Michel. Development of a multicriteria tool for optimizing the renovation of buildings, Applied Energy, 88, Elsevier Ltd (2011), pp. 1386-1394


CBC News. (2016, 10 5). CBC News. Retrieved2, 14, 2017, from: 〈http://www.cbc.ca/news/canada/montreal/mcgill-concordia-quebec-buildings-university-1.3793180〉

Y. Chang, Z. Huang, R. j Ries, E. Masanet. The embodied air pollutant emissions and water footprints of buildings in China: a quantification using disaggregated input–output life cycle inventory model, Journal of Cleaner Production, 113 (2016), pp. 274-284

J.L. Cohon. Multi-objective Programming and Planning, Academic Press, New York (1978)

R. Crawford. Validation of a hybrid life-cycle inventory analysis method, Journal of Environmental Management, 88 (2008), pp. 496-506

K. Deb, A. Partap, S. Agarwal, T. Meyarivan. A fast and elitist multiobjective genetic algorithm: NSGA-II, 6, IEEE Transactions on Evolutionary Computation (2002), pp. 182-197

K. DebMulti-objective optimization using evolutionary algorithms [Book], John Wiley and Sons, New York (2001)

N. Delgarm, B. Sajadi, F. Kowsary, S. Delgarm. Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO), Applied Energy, 170 (2016), pp. 293-303

DesignBuilder Software Ltd. (2016). DesignBuilder. Retrieved 1, 1, 2016, from 〈https://www.designbuilder.co.uk/〉

A.B. de Vasconcelos, M.D. Pinheiro, A. Manso, A. Cabaço. A Portuguese approach to define reference buildings for cost-optimal methodologies, Applied Energy, 140 (2015), pp. 316-328

P. De Wilde. The gap between predicted and measured energy performance of buildings: A framework for investigation, Automation in Construction, 41 (2014), pp. 40-49


C. DiLouieLighting Controls Handbook, Illuminating Engineering Society, NY (2008)

U. Diwekar. Introduction to Applied Optimization, Springer Science and Business Media (2013)

DOE-2, Retrieved 1, 5, 2016, from 〈http://doe2.com〉

e-QUEST, Retrieved 11, 1, 2015, from 〈http://doe2.com/equest/〉

C. Eastman, P. Teicholz, R. Sacks, K. Liston. BIM handbook: a guide to building information modeling for owner, managers, designers, engineers, and contractors, John Wiley& Sons, New York (2008)

R. EvinsA review of computational optimisation methods applied to sustainable building design, Renewable and Sustainable Energy Reviews, 22, Elsevier (2013), pp. 230-245

EurostatEnvironment and Energy Europe in figures: Eurostat yearbook., Office for Official Publications of the European Communities, Luxembourg (2010)

I. Flores-colen, J. De Brito. A systematic approach for maintenance budgeting of buildings façades based on predictive and preventive strategies, Construction and Building Materials, 24, Elsevier Ltd (2010), pp. 1718-1729

N. Galiotto, P. Heiselberg, M.A. KnudstrupIntegrated Renovation Process Overcoming Barriers to Sustainable Renovation, Journal of Architectural Engineering, 21 (3) (2015), p. 04015007 /gbXML site. Retrieved 7, 7, 2015, from 〈http://www.gbXML.org/〉. last reviewed, 12/12/2017.

D.E. GoldbergGenetic algorithms in search, optimization and machine learning., Addison Wesley (1989)

G. Giebeler, H. Krause, R. Fisch, F. Musso, B. Lenz, A. Rudolphi. Refurbishment manual: maintenance, conversions, extensions. Walter de Gruyter (2009)

Häkkinen, T. and Kiviniemi, A. (2008). Sustainable building and BIM, Melbourne, Australia.

J.H. Holland. Adaptation in natural and artificial systems: an introductory analysis with applications to biology [Book]
control, and artificial intelligence, University of Michigan Press, USA (1975)

J. Huang, H. Lv, T. Gao, W. Feng, Y. Chen, T. ZhouT. hermal properties optimization of envelope in energy-saving renovation of existing public buildings, Energy and Buildings, 75, Elsevier B.V (2014), pp. 504-510
Intergovernmental Panel on Climate Change. Climate Change 2007, The Physical Science Basis, Switzerland, WMO (2007)

International Alliance for Interoperability (IAI). (2006). IFC Model View Definition. Retrieved 1, 11, 2016, from 〈http://www.blis-project.org/IAI-MVD/〉.

L. Itard, F. Meijer.Towards a sustainable Northern European housing stock, Vol. 22, Delft Center for Sustainable Urban Areas, Amsterdam (2008)

F. Jalaei, A. Jrade. Integrating Building Information Modeling (BIM) and energy analysis tools with green building certification system to conceptually design sustainable buildings, Journal of Information Technology in Construction, 19 (2014), pp. 494-519

Jin, Q., and Overend, M. (2012). Facade renovation for a public building based on a whole-life value approach. First Building Simulation and Optimization Conference, 417–424.

Y.K. Juan, P. Gao, J. Wang. A hybrid decision support system for sustainable office building renovation and energy performance improvement, Energy and Buildings, 42 (2010), pp. 290-297

C.J. Kiber. tSustainable construction: green building design and delivery, New Jersey, Wiley, Hoboken (2008)

D. Kolokotsa, D. Rovas, E. Kosmatopoulos, K. KalaitzakisA roadmap towards intelligent net zero- and positive-energy buildings, Solar Energy, 85 (12) (2011), pp. 3067-3084

T. Konstantinou. Façade refurbishment toolbox, Delft University of Technology, Faculty of Architecture and The Build Environment (2014)

S. Kumar. Interoperability between Building Information Modeling (BIM) and energy analysis programs. MSc thesis, University of southern California, USA (2

R. Loonen, S. Singaravel, M. Trčka, D. Cóstola, J. Hensen. Simulation-based support for product development of innovative building envelope components, Automation in Construction, 45 (2014), pp. 86-95

H. Nakayama, Y. Yun, M. Yoon. Sequential Approximate Multiobjective Optimization Using ComputationIntelligence [Book] Springer-Verlag Berlin Heidelberg, Berlin (2009)

Natural Resources Canada. (2015). Survey of Commercial and Institutional Energy Use (SCIEU), Buildings, Retrieved from Natural Resources Canada. Retrieved 1, 8, 2016, from 〈https://oee.nrcan.gc.ca/corporate/statistics/neud/dpa/data_e/databases.cfm〉

A.-T. Nguyen, S. Reiter, P. Rigo. A review on simulation-based optimization methods applied to building performance analysis, Applied Energy, 113, Elsevier Ltd (2014), pp. 1043-1058

J. Ouyang, J. Ge, K. Hokao. Economic analysis of energy-saving renovation measures for urban existing residential buildings in China based on thermal simulation and site investigation., 37 (2009), pp. 140-149

Palonen, M., Hasan, A., and Siren, K. (2009). A Genetic Algorithm For Optimization Of Building Envelope


P. Penna, A. Prada, F. Cappelletti, A. Gasparella. Multi-objectives optimization of Energy Efficiency Measures in existing buildings, Energy and Buildings, 95, Elsevier B.V (2015), pp. 57-69

Schwartz, Y., Raslan, R., and Mumovic, D. (2015). Multi-objective genetic algorithms for the minimisation of the life cycle carbon footprint and life cycle cost of the refurbishment of a residential complex's envelope: a case study. SimAUD ’15 Proceedings of the Symposium on Simulation for Architecture & Urban Design, 189–196.

S. Sharif, A. Hammad. Simulation-based optimization of building renovation considering energy consumption and life-cycle assessment. International Workshop on Computing in Civil Engineering (IWCCE2017), University of Washington, Seattle (2017)

Statistics Canada, (2008). Retrieved 1, 9, 2015, from,〈https://www45.statcan.gc.ca/2008/cgco_2008_000-eng.htm〉

J. Straube, E. BurnettBuilding Science for Building Enclosures (Book), Westford, Mass, Building Science Press Inc. (2005)

P. Tuominen, K. Klobut, A. Tolman, A. Adjei, M. de Best-Waldhober. Energy savings potential in buildings and overcoming market barriers inmember states of the European union, Energy Build., 51 (2012), pp. 48-55

U.E.P.A. (2011). U.E.P.A. 2011 Green building-basic information. Retrieved 1, 1, 2015, from〈http://www.epa.gov/greenbuilding/pubs/about.htm〉.

U.S. Environmental Protection AgencyStrategic sustainability performance plan, U.S. Environmental Protection Agency (2011)

USGBC US Green Building Council (USGBC), LEED is green building Retrieved 5, 5, 2017, from 〈https://new.usgbc.org/leed〉.

M. Vandenbroucke, W. Galle, N. De Temmerman, W. Debacker, A. PaduartUsing life cycle assessment to inform decision-making for sustainable buildings, Buildings, 5 (2) (2015), pp. 536-559

W. Wang, H. Rivard, R. ZmeureanuAn object-oriented framework for simulation-based green building design optimization with genetic algorithms, Advanced Engineering Informatics, 19 (2005), pp. 5-23

M. Wetter, J. WrightA comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization, Building and Environment, 39 (8) (2004), pp. 989-999

WCED. (1987). Our common future. World Commission on Environment and Development. New York: Oxford.

P. Wilde. The gap between predicted and measured energy performance of buildings: A framework for investigation, Automation in Construction, 41 (2014), pp. 40-49