|本期目录/Table of Contents|

[1]胡觉亮,杨航,张田会,等.无人机与卡车协同配送优化研究[J].浙江理工大学学报,2020,43-44(社科五):489-497.
 HU Jueliang,YANG Hang,ZHANG Tianhui,et al.Research on cooperative distribution optimization of UAVs and Trucks[J].Journal of Zhejiang Sci-Tech University,2020,43-44(社科五):489-497.
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无人机与卡车协同配送优化研究()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第43-44卷
期数:
2020年社科五期
页码:
489-497
栏目:
出版日期:
2020-10-16

文章信息/Info

Title:
Research on cooperative distribution optimization of UAVs and Trucks
文章编号:
1673-3851 (2020) 10-0489-09
作者:
胡觉亮杨航张田会韩曙光
1.浙江理工大学,a.理学院;b.经济管理学院,杭州310018;2.北京机电工程研究所,北京100074;3.阿尔伯塔大学计算科学系,埃德蒙顿T6G 2E8,加拿大
Author(s):
HU Jueliang YANG Hang ZHANG Tianhui HAN Shuguang
1.a.School of Science; b.School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou 310018, China; 2.Beijing Electromechanical Engineering Institute, Beijing 100074, China;3. Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada
关键词:
无人机卡车协同路径规划人工蜂群算法
分类号:
F572
文献标志码:
A
摘要:
近年来出现了将卡车作为单架无人机着陆和起飞平台的配送模式。为进一步研究该模式对物流配送的价值,建立了一辆卡车搭载多架无人机为客户进行配送,同时考虑无人机限载、电量及客户时间窗等因素,以总配送成本最低为目标的混合整数规划模型,设计了嵌入改进节约里程算法(CW算法)的人工蜂群算法,通过与Lingo计算小规模算例精确解对比验证算法的有效性,同时对模型参数进行了敏感度分析。研究结果表明:所建立的模型及设计的算法是有效的,可以为城市物流配送中无人机的应用提供指导。

参考文献/References:

[1] 中国产业信息网. 2018年中国物流行业发展现状及发展趋势分析. (2018-04-08)[2019-10-01]. http://www.chyxx.com/industry/201804/627420.html.
[2] 郑翔. 无人机物流业发展的法律障碍和立法思考[J]. 北京交通大学学报(社会科学版), 2018, 17(1):136-142.
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[6] Ha Q M, Deville Y, Pham Q D, et al. On the mincost Traveling Salesman Problem with drone[J]. Transportation Research Part C: Emerging Technologies, 2018, 86:597-621.
[7] Choi Y. Optimization of multipackage drone deliveries considering battery capacity[C]// 96th Annual Meeting of the Transportation Research Board. Washington DC: 2017: 1-16.
[8] Dorling K, Heinrichs J, Messier G G, et al. Vehicle Routing Problems for drone delivery[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(1): 70-85.
[9] Sergio M F, Timothy H, Troy W, et al. Optimization of a truckdrone in tandem delivery network using kmeans and genetic algorithm[J]. Journal of Industrial Engineering and Management, 2016, 9(2):374-388.
[10] Ham A M. Integrated scheduling of mtruck, mdrone, and mdepot constrained by timewindow, droppickup, and mvisit using constraint programming[J]. Transportation Research Part C: Emerging Technologies, 2018, 91:1-14.

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备注/Memo

备注/Memo:
收稿日期:2019-10-23
网络出版日期:2020-01-17
基金项目:国家自然科学基金项目(11471286,11971435);浙江省自然科学基金项目(LQ17A010011)
作者简介:胡觉亮(1958-),男,浙江杭州人,教授,主要从事运筹学理论与应用方面的研究
通信作者:韩曙光,E-mail:zist001@163.com
更新日期/Last Update: 2020-11-04