A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment

Jiasen Wang; Jun Wang

doi:10.1109/ICIST55546.2022.9926802

A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In this paper, a continuous-time dual neural network model for linear assignment is presented. The model is based on a dual formulation of the primal linear assignment problem. Global convergence of the dual neural network is ensured under given conditions and assumptions. The dual neural network is compact in the sense that its number of neurons is the same as the number of agents. Simulation results on selecting communication paths with deterministic delay and jitter quality of services in networks and assigning multiple vehicles to formation targets are presented to substantiate the efficacy of the dual neural network model.

Original language	English
Title of host publication	2022 12th International Conference on Information Science and Technology (ICIST)
Publisher	IEEE
Pages	325-331
ISBN (Electronic)	9781665485821
ISBN (Print)	978-1-6654-9738-1
DOIs	https://doi.org/10.1109/ICIST55546.2022.9926802
Publication status	Published - 2022
Event	12th International Conference on Information Science and Technology (ICIST 2022) - Zhongzhou Huayue International Hotel (开封中州华悦国际饭店), Kaifeng, Henan, China Duration: 14 Oct 2022 → 16 Oct 2022 https://conference.cs.cityu.edu.hk/icist/

Publication series

Name	International Conference on Information Science and Technology, ICIST
ISSN (Print)	2164-4357
ISSN (Electronic)	2573-3311

Conference

Conference	12th International Conference on Information Science and Technology (ICIST 2022)
Place	China
City	Kaifeng, Henan
Period	14/10/22 → 16/10/22
Internet address	https://conference.cs.cityu.edu.hk/icist/

Funding

This work was supported in part by National Key Research and Development Program of China (Grant No. 2020YFB1805200, No. 2020YFB1806400), in part by the Research Grants Council of the Hong Kong Special Administrative Region of China under Grants 11202318 and 11203721.

Research Keywords

deterministic networking
Dual neural network
task assignment
vehicle target assignment

RGC Funding Information

RGC-funded

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10.1109/ICIST55546.2022.9926802

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Wang, J., & Wang, J. (2022). A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment. In 2022 12th International Conference on Information Science and Technology (ICIST) (pp. 325-331). (International Conference on Information Science and Technology, ICIST). IEEE. https://doi.org/10.1109/ICIST55546.2022.9926802

@inproceedings{fdc82d976dfa4c19a02db71b48e3e8cf,

title = "A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment",

abstract = "In this paper, a continuous-time dual neural network model for linear assignment is presented. The model is based on a dual formulation of the primal linear assignment problem. Global convergence of the dual neural network is ensured under given conditions and assumptions. The dual neural network is compact in the sense that its number of neurons is the same as the number of agents. Simulation results on selecting communication paths with deterministic delay and jitter quality of services in networks and assigning multiple vehicles to formation targets are presented to substantiate the efficacy of the dual neural network model.",

keywords = "deterministic networking, Dual neural network, task assignment, vehicle target assignment",

author = "Jiasen Wang and Jun Wang",

year = "2022",

doi = "10.1109/ICIST55546.2022.9926802",

language = "English",

isbn = "978-1-6654-9738-1",

series = "International Conference on Information Science and Technology, ICIST",

publisher = "IEEE",

pages = "325--331",

booktitle = "2022 12th International Conference on Information Science and Technology (ICIST)",

address = "United States",

note = "12th International Conference on Information Science and Technology (ICIST 2022) ; Conference date: 14-10-2022 Through 16-10-2022",

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Wang, J & Wang, J 2022, A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment. in 2022 12th International Conference on Information Science and Technology (ICIST). International Conference on Information Science and Technology, ICIST, IEEE, pp. 325-331, 12th International Conference on Information Science and Technology (ICIST 2022), Kaifeng, Henan, China, 14/10/22. https://doi.org/10.1109/ICIST55546.2022.9926802

A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment. / Wang, Jiasen ; Wang, Jun.
2022 12th International Conference on Information Science and Technology (ICIST). IEEE, 2022. p. 325-331 (International Conference on Information Science and Technology, ICIST).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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N2 - In this paper, a continuous-time dual neural network model for linear assignment is presented. The model is based on a dual formulation of the primal linear assignment problem. Global convergence of the dual neural network is ensured under given conditions and assumptions. The dual neural network is compact in the sense that its number of neurons is the same as the number of agents. Simulation results on selecting communication paths with deterministic delay and jitter quality of services in networks and assigning multiple vehicles to formation targets are presented to substantiate the efficacy of the dual neural network model.

AB - In this paper, a continuous-time dual neural network model for linear assignment is presented. The model is based on a dual formulation of the primal linear assignment problem. Global convergence of the dual neural network is ensured under given conditions and assumptions. The dual neural network is compact in the sense that its number of neurons is the same as the number of agents. Simulation results on selecting communication paths with deterministic delay and jitter quality of services in networks and assigning multiple vehicles to formation targets are presented to substantiate the efficacy of the dual neural network model.

KW - deterministic networking

KW - Dual neural network

KW - task assignment

KW - vehicle target assignment

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DO - 10.1109/ICIST55546.2022.9926802

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-9738-1

T3 - International Conference on Information Science and Technology, ICIST

SP - 325

EP - 331

BT - 2022 12th International Conference on Information Science and Technology (ICIST)

PB - IEEE

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ER -

Wang J , Wang J. A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment. In 2022 12th International Conference on Information Science and Technology (ICIST). IEEE. 2022. p. 325-331. (International Conference on Information Science and Technology, ICIST). Epub 2022 Nov 3. doi: 10.1109/ICIST55546.2022.9926802

A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment

Abstract

Publication series

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Funding

Research Keywords

RGC Funding Information

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GRF: Neurodynamics-driven Optimization and Control of Intelligent Heating, Ventilation and Air Conditioning Systems

GRF: Intelligent Mission Planning and Tracking Control of Autonomous Surface Vehicles Based on Neural Computation

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A Dual Assignment Network with Applications in Deterministic Communication Path Selection and Multi-Vehicle Target Assignment

Abstract

Publication series

Conference

Funding

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

GRF: Neurodynamics-driven Optimization and Control of Intelligent Heating, Ventilation and Air Conditioning Systems

GRF: Intelligent Mission Planning and Tracking Control of Autonomous Surface Vehicles Based on Neural Computation

Cite this