Renovation is known to be a complicated type of construction project and prone to errors compared to new constructions. The need to carry out renovation work while keeping normal business activities running, coupled with strict governmental building renovation regulations, presents an important challenge affecting construction performance. Given the current availability of robust hardware and software, building information modeling (BIM) and optimization tools have become essential tools in improving construction planning, scheduling, and resource management. This study explored opportunities to develop a multi-objective genetic algorithm (MOGA) on existing BIM. The data were retrieved from a renovation project over the 2018–2020 period. Direct and indirect project costs, actual schedule, and resource usage were tracked and retrieved to create a BIM-based MOGA model. After 500 generations, optimal results were provided as a Pareto front with 70 combinations among total cost, time usage, and resource allocation. The BIM-MOGA can be used as an efficient tool for construction planning and scheduling using a combination of existing BIM along with MOGA into professional practices. This approach would help improve decision-making during the construction process based on the Pareto front data provided.

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