Air refueling extends aircraft range and endurance, but its operational value hinges on where the refueling airspace is placed and how tanker missions are sequenced. This paper addresses the joint optimization of refueling airspace planning and tanker scheduling, in which each receiver selects a refueling point from a continuous feasible interval along a fixed route. The upper level determines refueling point locations (continuous variables), while the lower level schedules multiple heterogeneous tankers (discrete combinatorial variables); the two levels are tightly coupled through spatiotemporal constraints and fuel propagation. We propose a bottleneck-driven decoupled update (BDDU) strategy built on the Whale Optimization Algorithm (WOA). BDDU extracts bottleneck states from lower-level scheduling feedback and applies per-dimension step-size control to damp the coupling amplification effect inherent in bi-level optimization. Across three scenarios of varying coupling intensities and scales, BDDU-WOA raises the feasibility rate from 50% (WOA baseline) to 90% (+40 percentage points; p<0.05, Fisher’s exact test). The gain stems from a bottleneck-aware, dimension-wise step-size control mechanism with an adaptive, parameter-free classification threshold and only two tunable parameters, adding roughly 10% computational overhead. The method is intended for pre-mission planning of large-scale air refueling operations.
Ma et al. (Wed,) studied this question.