Jing Tan

ORCID: 0000-0003-3350-6908
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About
Contact & Profiles
Research Areas
  • Supply Chain Resilience and Risk Management
  • Blockchain Technology Applications and Security
  • Quality and Supply Management
  • Privacy-Preserving Technologies in Data
  • Age of Information Optimization
  • Advanced Control Systems Optimization
  • Control Systems and Identification
  • Analog and Mixed-Signal Circuit Design
  • IoT and Edge/Fog Computing
  • Advanced Multi-Objective Optimization Algorithms
  • Mobile Crowdsensing and Crowdsourcing
  • Sustainable Supply Chain Management
  • Supply Chain and Inventory Management

Huawei German Research Center
2022-2024

Huawei Technologies (China)
2019-2020

The University of Western Australia
1971

We formulate computation offloading as a decentralized decision-making problem with autonomous agents. design an interaction mechanism that incentivizes agents to align private and system goals by balancing between competition cooperation. The provably has Nash equilibria optimal resource allocation in the static case. For dynamic environment, we propose novel multi-agent online learning algorithm learns partial, delayed noisy state information, reward signal reduces information need great...

10.1109/infocom48880.2022.9796717 article EN IEEE INFOCOM 2022 - IEEE Conference on Computer Communications 2022-05-02

Manufacturing companies typically use sophisticated production planning systems optimizing steps, often delivering near-optimal solutions. As a downside for schedule, have high computational demands resulting in hours of computation. Under norma l circumstances this is not issue if there enough buffer time before implementation the schedule (e.g. at night next day). However, case unexpected disruptions such as delayed part deliveries or defectively manufactured goods, planned may become...

10.3233/aic-200646 article EN AI Communications 2020-06-26

The Intelligent Transportation System (ITS) environment is known to be dynamic and distributed, where participants (vehicle users, operators, etc.) have multiple, changing possibly conflicting objectives. Although Reinforcement Learning (RL) algorithms are commonly applied optimize ITS applications such as resource management offloading, most RL focus on single In many situations, converting a multi-objective problem into single-objective one impossible, intractable or insufficient, making...

10.1109/tits.2024.3378007 article EN IEEE Transactions on Intelligent Transportation Systems 2024-03-27

If the switching criterion of a time-invariant 2nd-order plant is derived on basis energy balance during complete cycle for step-input disturbances, prediction process may be synthetised without implementing optimum curve.

10.1049/el:19710214 article EN Electronics Letters 1971-06-03
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