A BIM-simulated annealing approach to optimize cost, size, and environmental impact of building water networks.

Research aimed at mitigating the environmental impact (EI) of the building industry has been the subject of numerous studies. However, existing literature has primarily focused on the Life Cycle Assessment (LCA) of building materials, with limited attention to building-level water networks (WN) and the link between pipe sizing and EI. Traditional sizing methods aim to minimize costs, but the extent to which optimal sizing influences EI remains underexplored. This paper presents a multi-objective optimization framework for WN design that minimizes EI, cost, and computational demand. A BIM-based Simulated Annealing (BIM-SA) algorithm was developed using Autodesk Revit and Python to automate and evaluate design alternatives. A case study applied the framework across two building regions, demonstrating reductions in pipe sizing by one nominal diameter, and in some cases, by as much as two, while achieving lower environmental impact and cost. These findings highlight the benefits of coupling digital design environments with computational optimization to support sustainable infrastructure decisions. The adaptability of the method across contexts suggests that it can provide more integrated and performance-driven approaches to water system design. By advancing the EI assessment of internal WNs, this research supports a holistic understanding of building systems and smart, resource-efficient design strategies.