An Integrated Decision Support Model for Early Planning in Off-Site Construction Projects

The construction industry is evolving toward more standardized, supply chain-oriented, modular, and integrated practices. This research introduces a novel transition matrix-based mixed-integer linear programming (MILP) model that optimizes modular construction (MC) design alongside supply chain decisions. The model incorporates real-world factors, such as modular element selection, supplier identification, and process sequencing and timing. Its unique contribution lies in the simultaneous optimization of both design and supply chain decisions within a unified framework. The model also enables sensitivity analysis on design choices, supplier alternatives, and productivity, supporting robust scenario planning and risk mitigation. Applied to both small and large-scale instances, the model proves computationally efficient and practical for real-world use. Results show that higher upfront investments in MC lead to improved inventory control, lower onsite costs, significantly shorter project durations, up to 44% faster completion, and 86% reduction in onsite work. The model fills existing research gaps by integrating decisions of MC, supply chain, and project management, offering a valuable project planning tool for general contractors. The model enhances early-phase decision making, collaboration, and cost-effectiveness while providing detailed insights into supplier management and the performance impact of modularity.