Integrating the Digital Twin into Elastic Cost Optimization for Legally Defensible Construction Schedule Management

This paper presents a hybrid methodology to combat endemic time and cost overruns in construction, particularly in emerging markets. The study fills a critical gap by integrating three advanced techniques into a single, coherent framework. First, the project schedule is determined by a mixed-integer linear programming (MILP) model that elastically optimizes time and costs, moving beyond simplistic linear models to account for realistic, nonlinear costs and diminishing returns associated with accelerating project activities. Second, this optimized schedule is rigorously validated through Monte Carlo simulation, which models and quantifies the probabilistic risk of meeting contractual deadlines under real-world uncertainty, transforming a deterministic plan into a risk-informed one with quantifiable confidence levels. Finally, this combined optimization-simulation engine is integrated into a digital twin (DT) platform, which operates as a dynamic system by integrating real-time field data to enable dynamic replanning when conditions change and, importantly, to generate a traceable, data-rich audit trail. This approach, applied to a Moroccan real estate project, provides more realistic cost-time tradeoffs than traditional assumptions, and becomes legally defensible and invaluable for supporting claims, justifying resource allocation, and strengthening a party’s position in contractual disputes.