Effective management of construction sites plays a critical role in improving project productivity, safety, and coordination of on-site activities. One of the key issues in construction site management is determining an appropriate location for the supervisory building, in a way that ensures efficient access to different parts of the site, enables effective monitoring of operations, and reduces potential safety risks. Although extensive studies have been conducted in the field of construction site layout planning, limited attention has been paid to optimizing the location of the supervisory building as a key managerial facility. This study proposes an optimization model for determining the optimal location of a site supervisory building using the Ant Colony Optimization (ACO) algorithm. In the proposed model, the construction site is divided into a set of potential candidate locations, and a weighted objective function is defined to evaluate each alternative based on operational criteria including accessibility to major work zones, monitoring capability, and safety considerations. The problem is formulated as a combinatorial optimization problem and solved using the Ant Colony Optimization algorithm. This algorithm is selected due to its strong capability in exploring large search spaces and identifying near optimal solutions for complex optimization problems. To evaluate the performance of the proposed model, three different scenarios with varying site conditions were designed and implemented in the MATLAB environment. The results indicate that the ACO algorithm can efficiently identify suitable locations for the supervisory building within a reasonable computational time. The findings suggest that metaheuristic optimization approaches can serve as effective decision-support tools for project managers during the construction site planning stage.