The overlapping coalition formation (OCF) game has emerged as a key framework in multi-agent systems, enabling unmanned aerial vehicles (UAVs) to participate in multiple distinct coalitions simultaneously. This paper studies constrained task allocation in heterogeneous UAV systems using OCF, with a focus on resource heterogeneity, communication constraints, and temporal limitations. We introduce an adaptive exploration–exploitation mechanism that systematically refines the solution space while avoiding premature convergence in coalition optimization. Comparative simulations with state-of-the-art OCF methods and variable neighborhood search (VNS) demonstrate that our approach significantly improves performance in resource-limited settings, achieving a 24.57