A novel decision support system for integrating supply chain and project management decisions to optimize multiple project performance: a case study in building renovation

Effective construction supply chain (CSC) management remains a critical challenge, particularly during pre-construction, where coordination across multiple projects is essential. While previous research has explored planning and scheduling in isolation, limited attention has been given to integrating master planning and scheduling with detailed planning and scheduling within a unified framework. This study addresses this gap by developing a novel decision support system (DSS) that combines heuristic methods with a mixed-integer linear programming (MILP) model to optimize integrated CSC planning for multi-project environments. The DSS supports strategic decisions involving resource allocation (renewable and non-renewable), skill assignment, scheduling, and supplier selection. Applied and tested in collaboration with a Canadian construction firm specializing in building renovations, the proposed system demonstrates superior scalability compared to a standalone MILP approach—effectively managing large-scale scenarios involving up to 80 concurrent projects. Sensitivity analyses confirm the robustness of the heuristic-based model in enhancing project scheduling accuracy and resource coordination. The findings suggest that the DSS can significantly improve project completion times, workforce utilization, supplier engagement, and inventory control, offering a practical and impactful solution for CSC managers during the pre-construction phase.