🤖 AI Summary
This study addresses the problem of reserving time-windowed airspace corridor capacity for low-altitude drone logistics under demand uncertainty to maximize expected net revenue. The authors propose a two-stage stochastic programming model: in the first stage, reserved capacities are determined for each corridor–time slot pair; in the second stage, realized delivery requests are routed through the network, explicitly capturing the coupling characteristics that capacity is non-transferable and jointly consumed along spatiotemporal paths. Innovatively integrating endogenous capacity reservation with route selection, the work establishes the equivalence between arc-flow and path-packing formulations and develops a Benders decomposition algorithm accelerated by column generation to efficiently obtain integer solutions. Computational experiments demonstrate single-digit LP-Benders gaps on medium-scale networks and scalability to large instances; a case study of Shenzhen reveals that reservations concentrate in structurally central corridors and are highly sensitive to demand levels and pricing.
📝 Abstract
Regulators in China, the United States, and the European Union now provide low-altitude airspace access as priced, time-windowed corridor authorizations, booked in advance and forfeited if unused. We ask how much capacity a UAV logistics planner should reserve on each corridor--time unit before demand is realized, to maximize expected profit net of reservation cost. Reserved capacity cannot be transferred across corridors or time windows and is consumed jointly along time-respecting paths, so reservations are coupled through the network in ways that models with exogenous airspace capacity cannot capture. We formulate a two-stage stochastic program whose recourse selects and routes accepted requests on a time-expanded network, prove its arc-based and path-packing forms equivalent, and solve it by Benders decomposition with column-generated subproblems. The decomposition operates on the LP relaxation, and all reported reservation and routing decisions are recovered as integer plans. Computational experiments achieve single-digit LP-Benders gaps on moderate-sized networks and extend to much larger instances through a truncated-path approach. A Shenzhen case study shows reservations concentrating on structurally central corridors, with demand level and reservation price having more influence on the quantity of capacity reserved than the selection of corridors.