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<p>An orthogonal randomized Bregman projection method is proposed for solving linearly constrained optimization problems by orthogonalizing two randomly selected hyperplanes. The convergence properties are analyzed under both noise-free and noisy cases. The expected linear convergence rate of the proposed method is derived and the upper bound of the convergence rate is given, which is better than that of the randomized Bregman projection method. Numerical experiments verify the efficiency of the proposed method in terms of the number of iterations and CPU time.</p>

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An orthogonal randomized Bregman projection method for linearly constrained optimization problems

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Yu-Xin Ye,
  • Ze Wang,
  • Shu-Xin Miao,
  • Jun-Feng Yin,
  • Shao-Liang Zhang

摘要

An orthogonal randomized Bregman projection method is proposed for solving linearly constrained optimization problems by orthogonalizing two randomly selected hyperplanes. The convergence properties are analyzed under both noise-free and noisy cases. The expected linear convergence rate of the proposed method is derived and the upper bound of the convergence rate is given, which is better than that of the randomized Bregman projection method. Numerical experiments verify the efficiency of the proposed method in terms of the number of iterations and CPU time.