A novel flexible operation mode and mission planning method for shipborne helicopter groups

To address efficient operation scheduling of shipboard helicopter groups under multi-mission demands and limited deck space, a novel Flexible Operation Mode (FOM) was proposed. Mission grouping, deck operation processes, and mission time were flexibilized to construct a mission planning method. From the perspective of the deck operation lifecycle, the scheduling problem was modeled as a six-stage mixed-integer program. A bi-level optimization framework was introduced, prioritizing maximization of mission time window satisfaction and secondarily minimizing mean deck operation time. Spatial evolution during the transportation phase was managed via an offline trajectory library that converted high-dimensional constraints into low-dimensional parameter mappings, significantly reducing real-time solution complexity. A Leader-Follower Particle Swarm Optimization (LFPSO) algorithm was developed, featuring a three-stage stochastic priority encoding and a mission-chain-driven launch-recovery decoupling strategy to reduce decision coupling. A hierarchical population structure enhanced co-evolution of global search and local refinement. The case simulation results show that the proposed model and algorithm can effectively solve the deck operation scheduling problem in complex mission scenarios, and are significantly superior to the Continuous Operation Mode (COM) and the Fixed-process FOM (FFOM) in key performance indicators such as mission time window satisfaction, average deck operation time, and average mission flight time. Its effectiveness in enhancing system scheduling capability and performance stability has been verified. This research provides systematic support for the flexible construction and intelligent decision-making of ship aviation operation systems.