2023-09-28 14:46:10 +00:00
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abstract: 'The implementation of the autonomous unmanned aerial mobility is a game
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changer for the on-demand delivery service in the crowded urban setting.
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In this study, the first of its kind commercial unmanned aerial vehicle
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(UAV) urban delivery program in China is targeted. Different from the
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traditional ground pickup and delivery services, the aerial mode
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considers not only the time window constraints, but also the spatial
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conflicts incurred during the take-off and landing operations of UAVs.
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To obtain the optimal flying routes of the focused problem, a mixed
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integer programming model is formulated. Due to its inherent complexity,
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the optimal schedule cannot be attained within acceptable time via the
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off-the-shelf solvers. To help speed up the solving process, a
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branch-and-cut based exact algorithm is proposed, together with a series
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of customized valid inequalities. To further accelerate, a greedy
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insertion heuristic is designed to secure high-quality initial
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solutions. In the numerical section, it is observed that the algorithm
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proposed in this paper can help solve the real-life on-demand UAV
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delivery problem to near optimum (within 5\% optimality gap) within
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reasonable computation time (in 5 minutes). Note to Practitioners-With
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the increase of labor cost, the distribution cost increases very
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rapidly. In the meantime, the employment of automated vehicles for
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logistics reshapes the landscape of the urban last-mile delivery. As an
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efficient courier carrier, the unmanned aerial vehicle (UAV) is trending
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the autonomous delivery endeavour. When integrating UAVs into the urban
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delivery program, practitioners need to pay special attention to the
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scheduling of UAVs at the operational level in addition to the hardware
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of the UAVs. To help solve the UAV dispatch problem, we propose an
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online scheduling scheme, considering the spatial conflict constraints
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in the actual UAV operations. And an exact algorithm is designed to
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accelerate the solving process. Numerical experiments demonstrate that
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the proposed algorithm can achieve near optimal dispatch plan with 5\%
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optimality gap in 5 minutes. Furthermore, it is discovered that the
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demand pooling is an essential decision to make for UAV-based delivery.
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Longer pooling time can increase the UAV efficiency with more realized
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demand information, but too much pooling could lead to prolonged
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customer waiting and a low service level.'
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affiliation: 'Yi, WC (Corresponding Author), Zhejiang Univ Technol, Coll Mech Engn,
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Hangzhou 310023, Peoples R China.
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Pei, Zhi; Fang, Tao; Weng, Kebiao; Yi, Wenchao, Zhejiang Univ Technol, Coll Mech
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Engn, Hangzhou 310023, Peoples R China.'
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author: Pei, Zhi and Fang, Tao and Weng, Kebiao and Yi, Wenchao
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author-email: yiwenchao@zjut.edu.cn
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author_list:
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- family: Pei
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given: Zhi
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- family: Fang
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given: Tao
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- family: Weng
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given: Kebiao
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- family: Yi
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given: Wenchao
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da: '2023-09-28'
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doi: 10.1109/TASE.2022.3184324
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earlyaccessdate: JUN 2022
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eissn: 1558-3783
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files: []
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issn: 1545-5955
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journal: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
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keywords: 'Drones; Logistics; Autonomous aerial vehicles; Routing; Transportation;
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Job shop scheduling; Dynamic scheduling; UAV; urban aerial delivery;
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pickup and delivery; on-demand; branch-and-cut'
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keywords-plus: DRONE; BRANCH; PICKUP; TRUCK; CUT
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language: English
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month: JUL
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number: '3'
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number-of-cited-references: '25'
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pages: 1675-1689
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papis_id: 8c1218c28020f4b294dc2c11cbc817f2
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ref: Pei2023urbanondemand
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researcherid-numbers: fang, tao/IQU-3074-2023
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times-cited: '3'
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title: 'Urban On-Demand Delivery via Autonomous Aerial Mobility: Formulation and Exact
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Algorithm'
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2023-10-01 08:15:07 +00:00
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type: article
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2023-09-28 14:46:10 +00:00
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unique-id: WOS:000826426000001
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usage-count-last-180-days: '16'
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usage-count-since-2013: '41'
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volume: '20'
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web-of-science-categories: Automation \& Control Systems
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year: '2023'
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