A Hybrid Large Neighborhood Search for Solving the Unmanned Aerial Vehicle Routing Problem with Multi-depot

Abstract

The Unmanned aerial vehicles (UAVs) are widely used for inspection tasks both in the military and civilian areas in which the route planning problem could be critical. The Unmanned Aerial Vehicle Routing Problem with Multi-depot (MDUAVRP) is a combination and extension of the Unmanned Aerial Vehicle Route Planning (UAVRP) and the Multi-depot Vehicle Routing Problem (MDVRP), which determines a set of the route visited by a fleet of UAV to perform a set of tasks. The objective of the MDUAVRP is to minimize the total flight cost. A novel hybrid heuristic approach is proposed aiming at this problem. Our proposal combines Adaptive Large Neighborhood Search (ALNS) and Variable Neighborhood Descent (VND) algorithm. The experimental results verify the effectiveness of the proposed algorithm.