abstract: 'The implementation of the autonomous unmanned aerial mobility is a game

  changer for the on-demand delivery service in the crowded urban setting.

  In this study, the first of its kind commercial unmanned aerial vehicle

  (UAV) urban delivery program in China is targeted. Different from the

  traditional ground pickup and delivery services, the aerial mode

  considers not only the time window constraints, but also the spatial

  conflicts incurred during the take-off and landing operations of UAVs.

  To obtain the optimal flying routes of the focused problem, a mixed

  integer programming model is formulated. Due to its inherent complexity,

  the optimal schedule cannot be attained within acceptable time via the

  off-the-shelf solvers. To help speed up the solving process, a

  branch-and-cut based exact algorithm is proposed, together with a series

  of customized valid inequalities. To further accelerate, a greedy

  insertion heuristic is designed to secure high-quality initial

  solutions. In the numerical section, it is observed that the algorithm

  proposed in this paper can help solve the real-life on-demand UAV

  delivery problem to near optimum (within 5\% optimality gap) within

  reasonable computation time (in 5 minutes). Note to Practitioners-With

  the increase of labor cost, the distribution cost increases very

  rapidly. In the meantime, the employment of automated vehicles for

  logistics reshapes the landscape of the urban last-mile delivery. As an

  efficient courier carrier, the unmanned aerial vehicle (UAV) is trending

  the autonomous delivery endeavour. When integrating UAVs into the urban

  delivery program, practitioners need to pay special attention to the

  scheduling of UAVs at the operational level in addition to the hardware

  of the UAVs. To help solve the UAV dispatch problem, we propose an

  online scheduling scheme, considering the spatial conflict constraints

  in the actual UAV operations. And an exact algorithm is designed to

  accelerate the solving process. Numerical experiments demonstrate that

  the proposed algorithm can achieve near optimal dispatch plan with 5\%

  optimality gap in 5 minutes. Furthermore, it is discovered that the

  demand pooling is an essential decision to make for UAV-based delivery.

  Longer pooling time can increase the UAV efficiency with more realized

  demand information, but too much pooling could lead to prolonged

  customer waiting and a low service level.'
affiliation: 'Yi, WC (Corresponding Author), Zhejiang Univ Technol, Coll Mech Engn,
  Hangzhou 310023, Peoples R China.

  Pei, Zhi; Fang, Tao; Weng, Kebiao; Yi, Wenchao, Zhejiang Univ Technol, Coll Mech
  Engn, Hangzhou 310023, Peoples R China.'
author: Pei, Zhi and Fang, Tao and Weng, Kebiao and Yi, Wenchao
author-email: yiwenchao@zjut.edu.cn
author_list:
- family: Pei
  given: Zhi
- family: Fang
  given: Tao
- family: Weng
  given: Kebiao
- family: Yi
  given: Wenchao
da: '2023-09-28'
doi: 10.1109/TASE.2022.3184324
earlyaccessdate: JUN 2022
eissn: 1558-3783
files: []
issn: 1545-5955
journal: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
keywords: 'Drones; Logistics; Autonomous aerial vehicles; Routing; Transportation;

  Job shop scheduling; Dynamic scheduling; UAV; urban aerial delivery;

  pickup and delivery; on-demand; branch-and-cut'
keywords-plus: DRONE; BRANCH; PICKUP; TRUCK; CUT
language: English
month: JUL
number: '3'
number-of-cited-references: '25'
pages: 1675-1689
papis_id: 8c1218c28020f4b294dc2c11cbc817f2
ref: Pei2023urbanondemand
researcherid-numbers: fang, tao/IQU-3074-2023
times-cited: '3'
title: 'Urban On-Demand Delivery via Autonomous Aerial Mobility: Formulation and Exact
  Algorithm'
type: Article
unique-id: WOS:000826426000001
usage-count-last-180-days: '16'
usage-count-since-2013: '41'
volume: '20'
web-of-science-categories: Automation \& Control Systems
year: '2023'