A Hybrid Framework for Multi-Objective Construction Site Layout Optimization

Effective Construction Site Layout Planning (CSLP) ensures the organized placement and sizing of temporary facilities, enhancing workflow and logistical efficiency. Poorly planned layouts, however, can increase material handling times, create bottlenecks, and reduce productivity, ultimately leading to higher costs. The main objective of this study is to introduce a BIM-based hybrid framework for CSLP that integrates Systematic Layout Planning (SLP) with a Genetic Algorithm (GA), developed through a Design Science Research approach. This Construction Site Optimization Framework (CSOF) addresses CSLP as a multi-objective optimization problem, prioritizing efficient positioning of facilities while accounting for workflow intensity, safety, and manager preferences. The framework’s continuous-space modeling supports a realistic approach, moving beyond fixed-location models. Exploratory case studies demonstrated CSOF’s effectiveness, achieving 30.79% to 40.98% reductions in non-value-adding travel distances and adaptability across varied site conditions. In this way, this research provides a decision-support tool that balances automation with decision-maker input, enhancing layout efficiency and operational flexibility in construction site management.