UAVs Path Planning under a Bi-Objective Optimization Framework for Smart Cities

Unmanned aerial vehicles (UAVs) have been used extensively for search and rescue operations, surveillance, disaster monitoring, attacking terrorists, etc. due to their growing advantages of low-cost, high maneuverability, easy deployability. This study proposes a mixed-integer programming model under multi-objective optimization framework design trajectories that enable set UAVs execute surveillance tasks. The first objective maximizes the cumulative probability target detection aim mission planning success. second ensures minimization path length provide higher resource utilization goal. A two-step variable neighborhood (VNS) algorithm is offered, which addresses combinatorial issue determining near-optimal sequence cell visiting reach target. Numerical experiments simulation results are evaluated in numerous benchmark instances. Results demonstrate proposed approach can favorably support practical deployability purposes.