Volumetric Uncertainty Bounds and Optimal Configurations for Converging Beam Triple LIDAR
Anthony Brooms, Theodore Holtom
We consider the problem of forward uncertainty propagation for the converging beam triple LIDAR technology, used for measuring wind velocity passing through a fixed point in space. The size of the volumetric output uncertainty is related to the inverse of the volume of a parallelepiped of unit edge length, delineated by the Doppler LIDAR configuration. Optimal configurations for minimizing output uncertainty are discussed, whilst a grid search procedure for optimizing the value of the parallelepiped volume, subject to LIDAR orientation uncertainty constraints, is presented.
Optimal Incentive in Electric Vehicle Adoption
We study a bilevel model with a policymaker and a population of vehicle owners. The policymaker minimizes a cost function deciding the incentive to encourage the largest possible percentage of the fossil-fueled vehicle owners to buy an electric one. All players care about PM10 concentration. The policymaker imposes a traffic ban if the PM10 concentration exceeds a safety threshold. Traffic bans generate a cost to the owners of a fossil-fueled vehicle. We reduce the initial bilevel formulation to a single level problem, which is solved analytically.
An Optimization Model to manage UAVs in multitiered 5G network slices
Daniele Sciacca, Gabriella Colajanni
In this paper, we present a three-tier supply chain network model consisting of a fleet of UAVs organized as a FANET managed by a fleet of UAVs controllers, whose purpose is to provide 5G network slices on demand to users and devices on the ground. Our aim is to provide a system optimization perspective for the entire supply chain network, obtaing a constrained optimization problem for which we derive the associated variational inequality formulation. Also, qualitative properties in terms of existence and uniqueness of solution are provided.