wow-inequalities/02-data/intermediate/wos_sample/b8c16d1095bc6c5f284e420bd68f8f4e-pei-zhi-and-fang-t/info.yaml

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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'