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.
In multi-mission air operations, area-patrol missions and long-range missions typically share a limited tanker fleet while imposing different constraint structures: patrol refueling is bounded by hard time windows, whereas long-range missions are governed by restricted-zone avoidance, detour tolerances, and multi-segme...
Xu Ma, Fu-Ping Yu, Di Shen· Aerospace· 0 citations
Unmanned aerial vehicle (UAV) inspection of mountainous expressway networks involves continuously distributed tasks, coordination among multiple base stations, and uncertain flight time and energy consumption induced by no-fly-zone detours. This study develops an offline robust planning framework that jointly determine...
Jun-Tao Wang, Lun-Wei Zhou, Jing-Yang Liu et al.· Applied Sciences· 0 citations
Large-scale maritime activity, persistent shipping incidents, and complex marine environments continue to place substantial demands on maritime search and rescue (MSAR). Current MSAR systems do not fully capitalize on the complementary strengths of unmanned aerial vehicles (UAVs) and satellites for collaborative tracki...
Zhaoyang Liao, Z. Du, Hongyuan Zeng et al.· Journal of Marine Science an...· 0 citations
This study introduces a dynamic scheduling model for single-aircraft aerial surveying, designed to maximize productivity while managing various operational costs effectively. Utilizing the Markov Decision Process (MDP) framework, the model enables adaptive decision-making, allowing the aircraft to select actions such a...
Saad Jamil, Mohammad M. Aldurgam, Ahmad Baubaid· IISE Annual Conference &...· 0 citations
Floating Storage and Offloading (FSO) units remain a cornerstone of hydrocarbon
export in deepwater fields where pipeline infrastructure is uneconomical or technically
impractical. Tandem offloading, in which a shuttle tanker connects astern of the FSO
by means of a mooring hawser and floating cargo hose, is the dom...
Paul Chibuike Obetta, Nwakamma Ninduwezuor-Ehiobu, H. Olisakwe· International Journal of Mul...· 0 citations
Efficient and safe coordination of connected and automated vehicle (CAV) platoons at unsignalized intersections remains a critical challenge for smart city logistics. Existing hierarchical frameworks often suffer from sequential scheduling inefficiencies, non-convergent low-level control loops, stop-line singular deadl...
Song-Tao Gu, B. Ma· 2026 IEEE 22nd International...· 0 citations
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