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Distributed Stochastic Algorithm for Global Optimization in Networked System

Author

Listed:
  • Shengnan Wang

    (Zhejiang University)

  • Chunguang Li

    (Zhejiang University)

Abstract

This paper studies the distributed optimization problem, whose aim is to find the global minimizer of the sum of multiple agents’ local nonconvex objective functions in a networked system. To solve such a distributed global optimization problem, we propose a distributed stochastic algorithm and we give detailed analysis of the global convergence of the proposed algorithm.

Suggested Citation

  • Shengnan Wang & Chunguang Li, 2018. "Distributed Stochastic Algorithm for Global Optimization in Networked System," Journal of Optimization Theory and Applications, Springer, vol. 179(3), pages 1001-1007, December.
    • Handle: RePEc:spr:joptap:v:179:y:2018:i:3:d:10.1007_s10957-018-1355-9
    DOI: 10.1007/s10957-018-1355-9
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    References listed on IDEAS

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    1. Cher Ming Tan (ed.), 2008. "Simulated Annealing," Books, IntechOpen, number 37.
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    Cited by:

    1. Chuanye Gu & Lin Jiang & Jueyou Li & Zhiyou Wu, 2023. "Privacy-Preserving Dual Stochastic Push-Sum Algorithm for Distributed Constrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 22-50, April.

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