Yongkui Liu

Orcid: 0000-0003-2165-775X

Affiliations:

Xidian University, School of Mechano-Electronic Engineering, Xi'an, China
University of Auckland, New Zealand (former)
Beihang University, School of Automation Science and Electrical Engineering, Beijing, China (former)
Xidian University, School of Mechano-Electronic Engineering, Xi'an, China (PhD 2010)

According to our database¹, Yongkui Liu authored at least 33 papers between 2014 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Enterprise and service-level scheduling of robot production services in cloud manufacturing with deep reinforcement learning.

[BibT_eX]

[DOI]

J. Intell. Manuf., December, 2024

Federated deep reinforcement learning for dynamic job scheduling in cloud-edge collaborative manufacturing systems.

[BibT_eX]

[DOI]

Int. J. Prod. Res., 2024

An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Prod. Res., 2024

2023

A framework for development of digital twin industrial robot production lines based on a mechatronics approach.

[BibT_eX]

[DOI]

Int. J. Model. Simul. Sci. Comput., December, 2023

Digital twin for a robot assembly line: Architecture and implementation.

[BibT_eX]

[DOI]

Int. J. Model. Simul. Sci. Comput., December, 2023

Optimization of manufacturers based on agent in cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Model. Simul. Sci. Comput., December, 2023

Enterprises cooperation and government supervision strategies under the impact of COVID-19.

[BibT_eX]

[DOI]

Comput. Ind. Eng., November, 2023

Smart robotics for manufacturing.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., August, 2023

Logistics-involved task scheduling in cloud manufacturing with offline deep reinforcement learning.

[BibT_eX]

[DOI]

J. Ind. Inf. Integr., August, 2023

Hierarchical scheduling for multi-composite tasks in cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Prod. Res., February, 2023

Function block-enabled operation planning and machine control in Cloud-DPP.

[BibT_eX]

[DOI]

Int. J. Prod. Res., February, 2023

Effects of different resource-sharing strategies in cloud manufacturing: a Stackelberg game-based approach.

[BibT_eX]

[DOI]

Int. J. Prod. Res., January, 2023

Scheduling of decentralized robot services in cloud manufacturing with deep reinforcement learning.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., 2023

2022

A digital twin-based sim-to-real transfer for deep reinforcement learning-enabled industrial robot grasping.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., 2022

Logistics-involved service composition in a dynamic cloud manufacturing environment: A DDPG-based approach.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., 2022

Dual manipulator collaborative shaft slot assembly via MADDPG.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2022

2021

Model maturity-based model service composition in cloud environments.

[BibT_eX]

[DOI]

Simul. Model. Pract. Theory, 2021

Industrial Internet for Manufacturing.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., 2021

Logistics-involved QoS-aware service composition in cloud manufacturing with deep reinforcement learning.

[BibT_eX]

[DOI]

Robotics Comput. Integr. Manuf., 2021

2020

QoS-Aware Service Composition in Cloud Manufacturing: A Gale-Shapley Algorithm-Based Approach.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Syst., 2020

IoT - and blockchain-enabled credible scheduling in cloud manufacturing: a systemic framework.

[BibT_eX]

[DOI]

Proceedings of the 18th IEEE International Conference on Industrial Informatics, 2020

2019

A multi-agent architecture for scheduling in platform-based smart manufacturing systems.

[BibT_eX]

[DOI]

Frontiers Inf. Technol. Electron. Eng., 2019

Scheduling in cloud manufacturing: state-of-the-art and research challenges.

[BibT_eX]

[DOI]

Int. J. Prod. Res., 2019

Multi-objective optimisation of multi-task scheduling in cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Prod. Res., 2019

Cloud manufacturing: key issues and future perspectives.

[BibT_eX]

[DOI]

Int. J. Comput. Integr. Manuf., 2019

A framework for scheduling in cloud manufacturing with deep reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019

2017

Agent-based simulation platform for cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Model. Simul. Sci. Comput., 2017

Resource service sharing in cloud manufacturing based on the Gale-Shapley algorithm: advantages and challenge.

[BibT_eX]

[DOI]

Int. J. Comput. Integr. Manuf., 2017

A clustering network-based approach to service composition in cloud manufacturing.

[BibT_eX]

[DOI]

Int. J. Comput. Integr. Manuf., 2017

2016

An Extensible Model for Multitask-Oriented Service Composition and Scheduling in Cloud Manufacturing.

[BibT_eX]

[DOI]

J. Comput. Inf. Sci. Eng., 2016

2015

A method of 3D reconstruction based on panoramic cameras.

[BibT_eX]

[DOI]

Int. J. Model. Simul. Sci. Comput., 2015

A Modeling Framework for Resource Service Sharing in a Cloud Manufacturing System.

[BibT_eX]

[DOI]

Proceedings of the Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth, 2015

2014

Cloud manufacturing: a new manufacturing paradigm.

[BibT_eX]

[DOI]

Enterp. Inf. Syst., 2014

Yongkui Liu

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