A versatile optimization framework for sustainable post-disaster building reconstruction

Niloufar Izadinia, Elham Ramyar, Maytham Alzayer, Stephen H. Carr, Gianluca Cusatis, Vidushi Dwivedi, Daniel J. Garcia, Missaka Hettiarachchi, Thomas Massion, William M. Miller, Andreas Wächter*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 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.

Original languageEnglish (US)
JournalOptimization and Engineering
DOIs
StateAccepted/In press - 2022

Keywords

  • Building model
  • Earthquake resistant building
  • Mixed-integer nonlinear optimization
  • Multi-objective optimization
  • Post-disaster reconstruction
  • Sustainability

ASJC Scopus subject areas

  • Software
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Electrical and Electronic Engineering

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