AI-ENABLED COST AND SCHEDULE OPTIMIZATION MODELS FOR CONSTRUCTION PROJECT MANAGEMENT

Abstract

Cost overruns and schedule delays are persistent challenges in construction project management, often resulting from uncertainty, poor planning, and inefficient resource utilization. Traditional optimization techniques rely on deterministic models and expert judgment, which are inadequate for handling complex and dynamic project environments. This paper proposes AI-enabled cost and schedule optimization models for construction project management by integrating machine learning and intelligent optimization techniques. The proposed framework analyzes historical and real-time project data to predict cost and schedule deviations and recommends optimal mitigation strategies. Artificial intelligence models dynamically adjust resource allocation, sequencing, and budgeting decisions. Experimental evaluation demonstrates that the AI-based approach significantly reduces cost overruns and schedule delays compared to conventional methods. The results highlight the potential of AI-driven optimization for improving project performance and decision-making accuracy.