Decomposition based approach for multi-trip helicopter routing and scheduling problem in last-mile relief distribution and rescue operations

The study proposes a novel multi-trip emergency logistics model to aid decision-makers in planning post-disaster aerial logistics when helicopters are the only mode of transportation. The developed MILP model considers aerial transportation for workforce transfer, aid distribution, and rescue from the affected region. To accomplish the relief mission, the proposed model incorporates the operational limitations of helicopters, such as work time limit, cargo and passenger capacity, landing compatibility, and fuel consumption rate, to portray an accurate picture of aerial logistics. It uses in-flight and ground fuel consumption rates to predict the refuel requirements. It accounts for flight range and service time limits to satisfy pickup and delivery requests, considering a limited number of helicopters performing multi-trips in a one-to-many service network. Due to the NP-hardness of the Multi-Trip Helicopter Routing and Scheduling (MT-HRS) model, we consider Logic-Based Benders Decomposition (LBBD) algorithm augmented with valid inequalities. The proposed model and LBBD approach have been computationally examined in small, medium, and large-scale situations. The computational results show that the enhanced LBBD approach outperforms the Branch and Cut (B&C) approach in CPLEX, LBBD algorithm without enhancements, and solves small, medium, and large-sized cases, including larger one with 50 nodes and 12–14 helicopters in a reasonable time.