Research on Dynamic Scheduling Strategy of Multi-Platform Unmanned Helicopters Based on Improved TS Algorithm

In modern amphibious operations, the dynamic scheduling of shipborne unmanned helicopters faces challenges including highly uncertain operational environments, complex and variable mission requirements, and stringent resource constraints. To tackle this issue, this paper presents an integrated solution encompassing modeling, scheduling strategies, and optimization algorithms. First, a Dynamic Scheduling Model for Integrated Operation-Support Activities of Shipborne Unmanned Helicopters (SUH-DSMIOSA) is developed, which integrates mission temporal constraints, heterogeneous unmanned helicopter resources, and deck support resource constraints to achieve integrated modeling of operational tasks and support operations. Second, a Multi-Modal Disturbance-Aware Adaptive Rescheduling Strategy (MDAARS) is designed, which adaptively selects targeted rescheduling schemes by identifying disturbance types and establishes a differentiated evaluation system to quantify their effects. And then, an Improved Tabu Search algorithm (I-TS) is proposed, enhancing search efficiency and solution quality through adaptive tabu length adjustment, enhanced neighborhood operations, and an intelligent restart strategy. The results show that the I-TS algorithm achieved an average convergence speed improvement of 40.2% and a solution quality enhancement of 1.76%. The algorithm reaches a normalized efficiency of 0.98 within 10 iterations and maintains excellent stability throughout the entire convergence process. When facing disturbance events, the proposed algorithm reduces the mission change rate by an average of 20.1% and improves the rescheduling success rate by 2.8% compared to other algorithms. This research provides theoretical support and technical pathways for efficient dynamic scheduling of unmanned helicopters in amphibious operations.