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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

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.

Original language	English
Title of host publication	Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4388-4391
Number of pages	4
ISBN (Electronic)	9781538612439
DOIs	https://doi.org/10.1109/CCDC.2018.8407889
State	Published - 6 Jul 2018
Externally published	Yes
Event	30th Chinese Control and Decision Conference, CCDC 2018 - Shenyang, China Duration: 9 Jun 2018 → 11 Jun 2018

Publication series

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

Conference

Conference	30th Chinese Control and Decision Conference, CCDC 2018
Country/Territory	China
City	Shenyang
Period	9/06/18 → 11/06/18

Keywords

Artificial fish swarm algorithm
Improved artificial potential
Optimal path

Access to Document

10.1109/CCDC.2018.8407889

Cite this

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. In Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018 (pp. 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 et al. / 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. pp. 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. in 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., pp. 4388-4391, 30th Chinese Control and Decision Conference, CCDC 2018, Shenyang, China, 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 et al.
Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 4388-4391 (Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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. In Proceedings of the 30th Chinese Control and Decision Conference, CCDC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 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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Keywords

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