<p>Retrofitting projects play a critical role in enhancing the sustainability of existing structures, yet balancing time, cost, and environmental impact remains a significant challenge for decision-makers. This study introduces a Multi-Objective Particle Swarm Optimization (MOPSO) approach to achieve optimal trade-offs among these competing objectives. By leveraging MOPSO’s capability to explore Pareto-efficient solutions, the research provides a robust framework for sustainable decision-making in retrofitting projects. The model evaluates project scenarios based on key metrics such as time efficiency, cost minimization, and reduced carbon emissions. Through the application of MOPSO, the study generates a range of viable solutions, enabling project managers to make informed decisions tailored to specific sustainability goals. A case study is conducted to validate the model’s effectiveness, comparing its performance with conventional optimization techniques. The results demonstrate that MOPSO excels in balancing multiple objectives, delivering superior outcomes in sustainability metrics. This research contributes to the advancement of sustainable construction practices by offering a practical tool for optimizing retrofitting projects in alignment with environmental and economic priorities. The findings provide valuable insights for practitioners seeking to integrate sustainability into decision-making processes, addressing the pressing need for environmentally conscious infrastructure development.</p>