Fuel-Efficient Multi-Sortie Scheduling for Forestry Helicopter Spraying Using Hybrid Adaptive Large Neighborhood Search with Sortie Consolidation

Forestry helicopter spraying requires fuel-efficient allocation of coverage tasks to successive sorties. Coverage-path generation alone does not resolve this allocation under coupled pesticide depletion and load-dependent fuel consumption. We formulate a Multi-Sortie Routing Problem with Non-synchronous Dual Resources (MSRP-NDR) and develop Sortie-Consolidation Hybrid Adaptive Large Neighborhood Search (SC-HALNS) to minimize modeled fuel consumption under pesticide-capacity and fuel constraints. For fixed coverage paths generated by convex decomposition and the Vector Modeling Method, the framework combines adaptive destroy-and-repair search and randomized variable neighborhood descent, supplemented by whole-sortie consolidation. Only merges that preserve resource feasibility and reduce total modeled fuel consumption are accepted. Six GIS-derived forest instances with 10–102 tasks were evaluated using 20 runs per stochastic algorithm and a nominal 100 s search budget. Relative to the aviation-company practice method (ACPM), SC-HALNS reduced mean modeled fuel consumption by 1.31–7.87%. Exact paired sign tests with Holm correction favored SC-HALNS in 13 of 18 external comparisons. Accepted consolidations reduced returns to the base, potentially easing replenishment workload. These results support offline scheduling under the evaluated model assumptions; reported fuel savings are model-based estimates.