TY - JOUR
T1 - A versatile optimization framework for sustainable post-disaster building reconstruction
AU - Izadinia, Niloufar
AU - Ramyar, Elham
AU - Alzayer, Maytham
AU - Carr, Stephen H.
AU - Cusatis, Gianluca
AU - Dwivedi, Vidushi
AU - Garcia, Daniel J.
AU - Hettiarachchi, Missaka
AU - Massion, Thomas
AU - Miller, William M.
AU - Wächter, Andreas
N1 - Funding Information:
Vidushi Dwivedi was supported in part by the Resnick Family Social Impact Program of Northwestern’s Institute for Sustainability and Energy (ISEN) and the World Wildlife Fund (WWF). Daniel J. Garcia was supported by a Northwestern University Presidential Fellowship. Additional support was provided by Leslie and Mac McQuown. We thank Mike McMahon for help with coordination and comments on the paper and Jennifer B. Dunn for discussions providing a life cycle analysis perspective. We also thank Ah Kim, Can Divitoglu, and Giovanna Varalta, who created an initial version of the AMPL model as part of their project in the Northwestern course IEMS 394 IE Client Project Challenge.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022
Y1 - 2022
N2 - This paper proposes an optimization framework for sustainable post-disaster building reconstruction. Based on mathematical optimization, it is intended to provide decision makers with a versatile tool to optimize building designs and to explore the trade-off between costs and environmental impact (represented by embodied energy) of alternative building materials. The mixed-integer nonlinear optimization model includes an analytical building model that considers structural and safety constraints and incorporates regional building codes. Using multi-objective optimization concepts, Pareto-optimal designs are computed that represent the best trade-off designs from which a decision maker can choose when they take additional criteria into consideration. As a case study, we consider the design of a multi-room one-story masonry building in Nepal. We demonstrate how the framework can be employed to address a variety of questions, such as the optimal building design and material selection, the sensitivity of the decision to material prices, and the impact of regional safety regulation thresholds.
AB - This paper proposes an optimization framework for sustainable post-disaster building reconstruction. Based on mathematical optimization, it is intended to provide decision makers with a versatile tool to optimize building designs and to explore the trade-off between costs and environmental impact (represented by embodied energy) of alternative building materials. The mixed-integer nonlinear optimization model includes an analytical building model that considers structural and safety constraints and incorporates regional building codes. Using multi-objective optimization concepts, Pareto-optimal designs are computed that represent the best trade-off designs from which a decision maker can choose when they take additional criteria into consideration. As a case study, we consider the design of a multi-room one-story masonry building in Nepal. We demonstrate how the framework can be employed to address a variety of questions, such as the optimal building design and material selection, the sensitivity of the decision to material prices, and the impact of regional safety regulation thresholds.
KW - Building model
KW - Earthquake resistant building
KW - Mixed-integer nonlinear optimization
KW - Multi-objective optimization
KW - Post-disaster reconstruction
KW - Sustainability
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U2 - 10.1007/s11081-022-09766-9
DO - 10.1007/s11081-022-09766-9
M3 - Article
AN - SCOPUS:85140108861
JO - Optimization and Engineering
JF - Optimization and Engineering
SN - 1389-4420
ER -