A Versatile Optimization Framework For Sustainable Post-Disaster Building Reconstruction
Abstract
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 answer a variety of questions, such as the optimal building design and material selection, the sensitivity of the decision to the prices, and the impact of regional safety regulation thresholds.
Keywords
Cite
@article{arxiv.2111.13178,
title = {A Versatile Optimization Framework For Sustainable Post-Disaster Building Reconstruction},
author = {Niloufar Izadinia and Elham Ramyar and Maytham Alzayer and Stephen H. Carr and Gianluca Cusatis and Vidushi Dwivedi and Daniel J. Garcia and Missaka Hettiarachchi and Thomas Massion and William M. Miller and Andreas Wächter},
journal= {arXiv preprint arXiv:2111.13178},
year = {2022}
}