An Integrated Methodology for Optimizing Electrical Cable Path in Building Construction

The optimization of cable paths is a crucial challenge in building construction, where numerous technically feasible designs exist, each with significant costs and efforts. Finding the optimal cable route, particularly in complex buildings, is considered a critical decision. Various shortest path algorithms can be employed to identify the optimal path. However, not all algorithms perform well when faced with networks containing constraints. The Minimum Spanning Tree (MST) exhibit satisfactory performance in unconstrained and constraints networks. Furthermore, this study presents an integrated methodology that combines different software tools to facilitate rapid and systematic experimentation with various scenarios, enabling informed decision-making. The methodology involves converting Industry Foundation Class (IFC) files to data files (CSV format), transforming the data into a graph database (DB), importing the DB from Revit and Dynamo into Python, identifying different cable network types during building installation, and visualizing optimal paths generated by the MST algorithm in each network type. Results indicate that the MST algorithm yields good results in terms of cable length and running time.