Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm

Chen Tingbin; Zhang Peng; Gao Shuang; Zhang Qisong

doi:10.1109/CCDC.2018.8407889

Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm

Chen Tingbin
, Zhang Peng
, Gao Shuang
, Zhang Qisong

Dalian Neusoft University of Information
Dalian Jiaotong University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

8 引用（Scopus）

摘要

Aiming at the problem of dynamic target path planning for delivery vehicles in logistics system, an improved artificial potential field-fish swarm algorithm is proposed. The algorithm is used to meet the requirements of real-time changes in the known obstacle environment, considering all the influencing factors, to minimize the total cost of distribution and find the optimal path. The simulation results show that the algorithm is effective in the logistics system. Secondly, compared with the simple improved artificial potential field method, the experiment proves that the algorithm is obviously improved for the fuel consumption and distribution distance of the distribution vehicle. It proves the efficiency of the algorithm.

源语言	英语
主期刊名	Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
出版商	Institute of Electrical and Electronics Engineers Inc.
页	4388-4391
页数	4
ISBN（电子版）	9781538612439
DOI	https://doi.org/10.1109/CCDC.2018.8407889
出版状态	已出版 - 6 7月 2018
已对外发布	是
活动	30th Chinese Control and Decision Conference, CCDC 2018 - Shenyang, 中国期限: 9 6月 2018 → 11 6月 2018

出版系列

姓名	Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018

会议

会议	30th Chinese Control and Decision Conference, CCDC 2018
国家/地区	中国
市	Shenyang
时期	9/06/18 → 11/06/18

访问文件

10.1109/CCDC.2018.8407889

其它文件与链接

链接到 Scopus 的出版物

引用此

Tingbin, C., Peng, Z., Shuang, G., & Qisong, Z. (2018). Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm. 在 Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018 (页码 4388-4391). (Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC.2018.8407889

Tingbin, Chen ; Peng, Zhang ; Shuang, Gao 等. / Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm. Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 4388-4391 (Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018).

@inproceedings{45ac47d5251a4b1e95c3bb708560aa06,

title = "Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm",

abstract = "Aiming at the problem of dynamic target path planning for delivery vehicles in logistics system, an improved artificial potential field-fish swarm algorithm is proposed. The algorithm is used to meet the requirements of real-time changes in the known obstacle environment, considering all the influencing factors, to minimize the total cost of distribution and find the optimal path. The simulation results show that the algorithm is effective in the logistics system. Secondly, compared with the simple improved artificial potential field method, the experiment proves that the algorithm is obviously improved for the fuel consumption and distribution distance of the distribution vehicle. It proves the efficiency of the algorithm.",

keywords = "Artificial fish swarm algorithm, Improved artificial potential, Optimal path",

author = "Chen Tingbin and Zhang Peng and Gao Shuang and Zhang Qisong",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 30th Chinese Control and Decision Conference, CCDC 2018 ; Conference date: 09-06-2018 Through 11-06-2018",

year = "2018",

month = jul,

day = "6",

doi = "10.1109/CCDC.2018.8407889",

language = "英语",

series = "Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4388--4391",

booktitle = "Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018",

address = "美国",

}

Tingbin, C, Peng, Z, Shuang, G & Qisong, Z 2018, Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm. 在 Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018, Institute of Electrical and Electronics Engineers Inc., 页码 4388-4391, 30th Chinese Control and Decision Conference, CCDC 2018, Shenyang, 中国, 9/06/18. https://doi.org/10.1109/CCDC.2018.8407889

Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm. / Tingbin, Chen; Peng, Zhang; Shuang, Gao 等.
Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 页码 4388-4391 (Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm

AU - Tingbin, Chen

AU - Peng, Zhang

AU - Shuang, Gao

AU - Qisong, Zhang

PY - 2018/7/6

Y1 - 2018/7/6

N2 - Aiming at the problem of dynamic target path planning for delivery vehicles in logistics system, an improved artificial potential field-fish swarm algorithm is proposed. The algorithm is used to meet the requirements of real-time changes in the known obstacle environment, considering all the influencing factors, to minimize the total cost of distribution and find the optimal path. The simulation results show that the algorithm is effective in the logistics system. Secondly, compared with the simple improved artificial potential field method, the experiment proves that the algorithm is obviously improved for the fuel consumption and distribution distance of the distribution vehicle. It proves the efficiency of the algorithm.

AB - Aiming at the problem of dynamic target path planning for delivery vehicles in logistics system, an improved artificial potential field-fish swarm algorithm is proposed. The algorithm is used to meet the requirements of real-time changes in the known obstacle environment, considering all the influencing factors, to minimize the total cost of distribution and find the optimal path. The simulation results show that the algorithm is effective in the logistics system. Secondly, compared with the simple improved artificial potential field method, the experiment proves that the algorithm is obviously improved for the fuel consumption and distribution distance of the distribution vehicle. It proves the efficiency of the algorithm.

KW - Artificial fish swarm algorithm

KW - Improved artificial potential

KW - Optimal path

UR - https://www.scopus.com/pages/publications/85050857809

U2 - 10.1109/CCDC.2018.8407889

DO - 10.1109/CCDC.2018.8407889

M3 - 会议稿件

AN - SCOPUS:85050857809

T3 - Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018

SP - 4388

EP - 4391

BT - Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 30th Chinese Control and Decision Conference, CCDC 2018

Y2 - 9 June 2018 through 11 June 2018

ER -

Tingbin C, Peng Z, Shuang G, Qisong Z. Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm. 在 Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 页码 4388-4391. (Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018). doi: 10.1109/CCDC.2018.8407889

Research on the dynamic target distribution path planning in logistics system based on improved artificial potential field method-fish swarm algorithm

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出版系列

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