## 4 Discussion
These features enable project managers to identify instances where a resource is overbooked or assigned to different tasks during the same period, leading to potential overallocation [18]. However, the methods lack the capability to handle situations where a single activity is overloaded or where the requirements are of mixed heterogeneous types. Construction sites are inherently dynamic environments where numerous activities compete for limited space. By proactively identifying, preventing, and resolving spatial conflicts in construction planning, projects can achieve improved efficiency, enhanced safety, and, ultimately, greater project success. Various optimization methods have been explored to resolve spatial conflicts in construction projects, such as genetic algorithms (GAs) [19; 20], particle swarm optimization (PSO) [21], and the building displacement operation (BDGSA) [22]. Alongside optimization approaches, leveraging discrete event simulation (DES) and Unity-based path planning offers a promising automated solution for identifying and resolving potential time-space conflicts [23]. However, the necessity of integrating these algorithms with project planning processes remains a challenge that needs to be addressed. Several studies propose integrating 4D/5D planning with advanced tools for conflict management in construction projects. One such example is the nD Planning System, which integrates workspace management with critical path method (CPM) scheduling and building information modeling (BIM) data [24]. It provides analytical capabilities for conflict resolution, including adjusting activity schedules, modifying workspace sizes and locations, and exploring alternative construction methods. Nevertheless, a potential limitation of this approach lies in its iterative conflict resolution process, where conflicts are tackled one by one, which may not be optimal for highly complex projects with intricate dependencies. Our proposed approach addresses limitations in existing methods by incorporating two additional modules that enhance resource management in a practical and efficient way. These modules focus on proactive conflict identification and real-time resource availability verification before tasks commence. While this combined approach may extend the overall project duration, it represents a strategic trade-off. A marginally prolonged yet demonstrably more feasible and executable schedule is a prudent compromise, as it mitigates the risks associated with unforeseen delays, rework, or safety incidents that could potentially arise due to resource incompatibility or unavailability issues. In this study, the identified spatial overlaps and resource overallocation necessitate delaying the upcoming task's initiation to adhere to stakeholder requirements. Beyond this primary function, the tool offers additional features successfully employed in other scenarios that could be adapted here. Notably, it can compare task priorities and recommend pausing the ongoing task if it has lower priority than the upcoming one. Alternatively, a user-defined rule-based algorithm could be implemented to highlight the tool's versatility. While the proposed solution offers significant advantages, it is essential to acknowledge its current limitations and outline potential future research directions. At present, Optimizio lacks a cloud-based solution, restricting its usage to local machines. This limitation hinders the ability to directly link team member information to simulations, potentially impacting collaboration and accessibility. To address this limitation, future developments should focus on creating a cloud-based solution for Optimizio. By transitioning to a cloud-based platform, users would gain the ability to access and run Optimizio simulations from anywhere with an internet connection. This enhancement would significantly improve accessibility and facilitate seamless collaboration among geographically dispersed teams.