Multiobjective Optimization Model for the Life Cycle Cost-Sustainability Trade-Off Problem of Building Upgrading Using a Generic Sustainability Assessment Tool
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 7
Abstract
Because existing buildings occupy most of our built environment, there is an urgent need to upgrade them considering building sustainability criteria. Therefore, many optimization models were proposed to find the optimum upgrading solution that improves the building sustainability while minimizing its costs using traditional sustainability rating tools [e.g., Leadership in Energy and Environmental Design (LEED) (US), Building Research Establishment Environmental Assessment Methodology (BREEAM) (UK), and others]. The variations among these tools hinder their application outside their original countries, calling for global tools. Therefore, this study contributes to the knowledge by developing a novel multiobjective optimization model to solve the life cycle cost (LCC)-sustainability trade-off for building upgrading using a generic sustainability rating tool. This tool includes seven sustainability criteria and 29 subcriteria, resulting in 134 decision variables. The proposed model finds the near-optimum upgrading solutions that minimize their LCC while improving the building sustainability using the multiobjective artificial immune system algorithm. The model was applied to a real case study of a large building in Montreal, Canada. The obtained solutions covered almost all the ratings ranges from pass to outstanding and showed the trade-offs between the building sustainability and LCC. This research is a step toward adopting a global sustainability rating tool to find the optimum building upgrading solutions that can address the regional limitations of the traditional rating tools.
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Data Availability Statement
Some or all data, models, or code that support this study’s findings are available from the corresponding author upon reasonable request.
Acknowledgments
No funding was provided for this research.
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Journal of Construction Engineering and Management
Volume 148 • Issue 7 • July 2022
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© 2022 American Society of Civil Engineers.
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Received: May 25, 2021
Accepted: Feb 3, 2022
Published online: Apr 22, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 22, 2022
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