Synchronized arrival coordination represents a critical challenge in multi-agent systems, particularly for military tactical operations, emergency response, and autonomous swarm robotics, where precise temporal coordination is essential. Traditional Ant Colony Optimization (ACO) algorithms optimize for shortest paths but fail to address the temporal synchronization requirements inherent in multi-agent coordination scenarios. We introduce MACO-Sync (Multi-Agent Ant Colony Optimization for Synchronized Arrival), a novel ACO variant that explicitly optimizes for temporal coordination rather than path minimization. Our key contribution is a synchronized pheromone update mechanism based on arrival time patterns. The agents’ pheromone contributions are weighted by their synchronization variance with other agents. Extensive experimental evaluation on tactical coordination scenarios demonstrates that MACO-Sync achieves 23.9 times better synchronization scores and 6.8 times lower arrival variance compared to baseline algorithms. Our approach enables effective multi-agent coordination without explicit inter-agent communication. This is particularly suitable for military and emergency response applications where communication constraints are prevalent. Code: GitHub repository .