Decision-making optimization method for construction site layout planning

Construction site layout planning (CSLP) can be conducted as an optimization problem to determine temporary facilities’ optimal layouts, adequate construction space allocations for equipment, and efficient on-site path plans. Although previous studies have reported advanced optimization approaches for site layout generation, such as mathematical models and computational algorithms, CSLP is often overlooked by professionals. Previous experience has been preferred over advanced optimization models by professionals due to the complexity and lack of flexibility in such automated solutions. Thus, this research involves decision-makers in CSLP, assuming that a knowledge-based rules method integrated with an optimization approach ensures more assertive solutions. Systematic Layout Planning (SLP) is a method used to effectively plan facility layouts in the manufacturing industry, applying rules to assess the need for proximity between facilities. Furthermore, Building Information Modeling provides an adequate framework to support the decision-making process. Through Design Science Research, this research aims to propose a method to support decision-making in the planning and logistics of construction sites. This study investigates the utility of an SLP-based genetic algorithm to achieve an optimized layout solution, using input data provided by the construction manager. Proximity relationships are determined according to the intensity of logistical flow between facilities, safety concerns and manager preferences. The artifact was developed with the collaboration of potential users through their continuous assessment of the method. The results show the effectiveness of the artifact by reporting the solution with the maximum decrease in weighted distances between the facilities.