Hierarchical Optimization of Scheduling Scheme for Mixed Helicopter Fleet in Disaster Relief

Helicopters with unique characteristics play a significant role in natural disaster rescue. Moreover, it is critical to make an efficient scheduling scheme for the helicopter fleet, which can meet all of the needs as soon as possible according to the rescue resource distribution in the disaster area. However, only a few references reported for the macro-scheduling problem of mixed helicopter fleets under complex needs can be found. Therefore, this paper focuses on the scheduling problem of helicopter fleets after natural disasters happening and proposes a hierarchical optimization method of mixed helicopter fleet scheduling scheme (HOMHFSS). The optimization of scheduling scheme in HOMHFSS was divided into two phases; one is mission assignment, and the other is route planning. Five algorithms were adopted in this work. The simulated annealing algorithm, genetic algorithm, and pseudo-particle swarm optimization algorithm were used at the phase of mission assignment. The branch and bound method and the adaptive ant colony algorithm were applied to find the best routes at the phase of route planning. The results of this investigation show that HOMHFSS can produce a decline of 0.51 h on average in the optimization of scheduling schemes, proving its effectiveness.