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Correction: Li et al. Recovery Behavior of the Macro-Cracks in Elevated Temperature-Damaged Concrete after Post-Fire Curing. <i>Materials</i> 2022, <i>15</i>, 5673.

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Simulation- and Metamodel-Based Multi-Objective Optimization for Sustainable Building Retrofit Across Climatic

Sk Reza-E-Rabbi1, Muhammed A Bhuiyan1, Guomin Zhang1,2

  • 1Civil and Infrastructure Engineering Department, School of Engineering, RMIT University, Melbourne 3001, Australia.

Materials (Basel, Switzerland)
|May 4, 2026
PubMed
Summary

This review synthesizes building retrofit optimization techniques, analyzing passive and active strategies across climates. It highlights the need for integrated, climate-responsive decision-making frameworks to improve energy performance and sustainability.

Keywords:
building retrofitclimatic conditionsmulti-objective optimizationoptimization frameworksustainable buildings

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Area of Science:

  • Building Science
  • Optimization Techniques
  • Sustainable Architecture

Background:

  • Building retrofits are crucial for enhancing energy performance and sustainability.
  • Existing research often focuses on optimization techniques or retrofit strategies independently.
  • A climate-specific analysis of retrofit suitability and performance is needed.

Purpose of the Study:

  • To review and synthesize simulation-based multi-objective optimization (SBMOO) and metamodel-based multi-objective optimization (MBMOO) techniques for building retrofits.
  • To analyze passive, active, and combined retrofit strategies considering climatic influences.
  • To propose a framework for structured selection of baseline modeling and optimization pathways in retrofit studies.

Main Methods:

  • Systematic review of 162 studies on building retrofit optimization.
  • Analysis of simulation-based (SBMOO) and metamodel-based (MBMOO) optimization approaches.
  • Evaluation of passive, active, and combined retrofit strategies across diverse climatic conditions.

Main Results:

  • Energy efficiency, comfort, cost-effectiveness, and environmental impact are key retrofit metrics.
  • SBMOO offers robust optimization but is computationally intensive; MBMOO is efficient but data-dependent.
  • Most studies are case-specific, limiting transferability; sustainability and social objectives are underexplored.

Conclusions:

  • There is a need for integrated approaches combining optimization pathways with climate-based retrofit strategy analysis.
  • A synthesized framework is proposed to guide future retrofit studies towards more consistent and climate-responsive decision-making.
  • Future research should address underutilized metrics like life cycle assessment and social objectives.