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Drone-Fleet-Enabled Logistics: A Joint Design of Flight Trajectory and Package Delivery.
Jia, Yunjian; Zhang, Yi; Luo, Kun; Wen, Wanli.
Afiliação
  • Jia Y; School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
  • Zhang Y; School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
  • Luo K; School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
  • Wen W; School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Sensors (Basel) ; 22(8)2022 Apr 15.
Article em En | MEDLINE | ID: mdl-35459039
ABSTRACT
In this work, we focus on a drone-fleet-enabled package delivery scenario, in which multiple drones fly from a start point and cooperatively deliver packages to the ground users in the presence of a number of no-fly zones (NFZs). We first mathematically model the package delivery scenario in a rigorous manner. Then, a package value maximization problem is established to optimize the flight trajectory and package delivery under the constraints of drone load and collision as well as NFZs. The formulated problem is a highly challenging mixed-integer non-convex problem. To facilitate solving it, we transform the formulated problem into an equivalent problem with special structure by using some appropriate transformations, based on which a low-complexity algorithm with favorable performance is developed using the penalty convex-concave procedure method. Finally, numerical results demonstrate the superiority of the proposed solution.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Dispositivos Aéreos não Tripulados Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Dispositivos Aéreos não Tripulados Idioma: En Ano de publicação: 2022 Tipo de documento: Article