• Aishwarya Thorat
• Ketan Ushir

Planning and scheduling play crucial roles in ensuring the successful execution of construction projects. However, the inherent complexity and uncertainty in the construction environment often challenge traditional planning and scheduling methods. In recent years, the construction industry has witnessed the emergence of powerful tools that combine simulation-based techniques with artificial intelligence (AI) to address these challenges. This study provides an overview of how construction planning and scheduling can be optimized using simulation-based techniques and AI. The proposed approach utilizes AI algorithms and machine learning techniques to analyse and interpret large volumes of construction-related data. This data includes information on resource availability, project scope, constraints, historical project data, and external factors such as weather conditions. AI models are trained using this data, learning from past project experiences to identify patterns and correlations that can inform the construction planning process. The integration of AI and simulation-based techniques offers several benefits in construction planning and scheduling optimization. Firstly, it enables more accurate forecasting of project outcomes and the identification of potential bottlenecks or risks. Secondly, it facilitates the exploration of various scenarios, assisting project managers in making informed decisions and selecting the most optimal plans. Furthermore, it enables real-time adjustments to the project schedule based on changing conditions, such as weather disruptions or unexpected events. This approach enhances the accuracy of project forecasting, allows for scenario exploration, and enables real-time adjustments, ultimately contributing to more successful and efficient construction project execution.

"AI-DRIVEN OPTIMIZATION OF CONSTRUCTION PROJECT SCHEDULING: MACHINE LEARNING APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.c177-c182, June-2024, Available :http://www.jetir.org/papers/JETIR2406224.pdf

"AI-DRIVEN OPTIMIZATION OF CONSTRUCTION PROJECT SCHEDULING: MACHINE LEARNING APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppc177-c182, June-2024, Available at : http://www.jetir.org/papers/JETIR2406224.pdf