creator Kim, Taehyoung advisor Arditi, David Material selection is an important part of building design because it has great impact on the environment, as buildings during/after construction are responsible for a large portion of carbon emissions and use many resources and considerable energy. Selecting green materials is an emergent issue in both design firms and construction companies. Green building certification such as LEED systems originated from the desire to improve environmental, economic, financial, and social benefits. The current approach to material selection for sustainability is based only on the designer’s past experiences. An arbitrary approach based on subjective opinions causes unnecessary expense, longer construction duration, and failure to meet desired environmental goals. In order to help decision-makers with the selection of the right materials, this study proposes a model that uses Genetic Algorithms in MATLAB and that optimizes the desired points in LEED Certification within budget constraints. This model can be applied to any project that is pursuing LEED Certification. If the user specifies the desired LEED points, the system recommends the least expensive combination of materials extracted from a database containing detailed information about a large member of materials. The modified model uses multi-objective genetic algorithms to establish trade-off between budget constraints and LEED points. The proposed system is expected to be a useful tool for inexperienced designers and a valuable guideline for designers with extensive experience. Submitted by Liana Khananashvili (khananashvili@iit.edu) on 2013-08-08T21:34:34Z No. of bitstreams: 2 Thesis_Taehyoung Kim_12.2012.pdf: 2095028 bytes, checksum: 485e55c4c38c6dc372f423ac1b757099 (MD5) Cover.pdf: 32649 bytes, checksum: a4bf00dbe06c141b43bbedce1e1f9cb6 (MD5) Made available in DSpace on 2013-08-08T21:34:34Z (GMT). No. of bitstreams: 2 Thesis_Taehyoung Kim_12.2012.pdf: 2095028 bytes, checksum: 485e55c4c38c6dc372f423ac1b757099 (MD5) Cover.pdf: 32649 bytes, checksum: a4bf00dbe06c141b43bbedce1e1f9cb6 (MD5) Previous issue date: 2012-12 M.S. in Civil Engineering, December 2012 2012-12-16 2012-12 http://hdl.handle.net/10560/3018 en Thesis born digital application/pdf In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access CAEE / Civil, Architectural, and Environmental Engineering Illinois Institute of Technology Affiliated department