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Distributed Neurodynamic Approach for Optimal Allocation with Separable Resource Losses

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Neural Information Processing (ICONIP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14447))

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Abstract

To solve the optimal allocation problem with separable resource losses, this paper proposes a neurodynamic approach based on multi-agent system. By using KKT condition, the nonlinear coupling equality constraint in the original problem is equivalently transformed into a convex coupling inequality constraint. Then, with the help of finite-time tracking technology and fixed-time projection method, a neurodynamic approach is designed and its convergence is strictly proved. Finally, simulation results verify the effectiveness of the proposed neurodynamic approach.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (No. 62176073, No. 12271127), Taishan Scholars of Shandong Province (No. tsqn202211090), and in part by the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology.

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Authors and Affiliations

  1. Harbin Institute of Technology, Weihai, 264200, China

    Linhua Luan, Yining Liu & Sitian Qin

  2. Shenzhen University, Shenzhen, 518060, China

    Jiqiang Feng

Authors
  1. Linhua Luan
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  2. Yining Liu
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  3. Sitian Qin
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  4. Jiqiang Feng
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Corresponding author

Correspondence to Sitian Qin .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Biao Luo

  2. Chinese Academy of Sciences, Beijing, China

    Long Cheng

  3. Zhejiang University, Hangzhou, China

    Zheng-Guang Wu

  4. Guangdong University of Technology, Guangzhou, China

    Hongyi Li

  5. UNSW Sydney, Sydney, NSW, Australia

    Chaojie Li

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Luan, L., Liu, Y., Qin, S., Feng, J. (2024). Distributed Neurodynamic Approach for Optimal Allocation with Separable Resource Losses. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Lecture Notes in Computer Science, vol 14447. Springer, Singapore. https://doi.org/10.1007/978-981-99-8079-6_13

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  • DOI: https://doi.org/10.1007/978-981-99-8079-6_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8078-9

  • Online ISBN: 978-981-99-8079-6

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