Algorithm Performance Benchmarks for Split Common Fixed Point Problems

A paper by Zheng Zhou from the University of Electronic Science and Technology of China presents an accelerated hybrid projection algorithm. The algorithm's reliability and robustness are illustrated through numerical experiments in infinite Hilbert space. The paper includes strong convergence theorems obtained under mild conditions.

Use Cases

• Benchmarking new optimization algorithms based on the described numerical experiments.
• Studying the convergence behavior of demicontractive mappings in Hilbert spaces.
• Comparing inertial and hybrid projection techniques for solving fixed point problems.

Strengths

• The algorithm uses a self-adaptive step-size sequence, eliminating the need for prior knowledge of operator norms.
• The paper provides strong convergence theorems under mild conditions.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Electronic Science and Technology of China

Collection Method

Algorithm development and numerical experiments.