A Novel Hybrid Conjugate Gradient Method for Constrained Nonlinear Monotone Equations

This study proposes a novel hybrid conjugate gradient method, termed the RMILLS method, aimed at resolving constrained nonlinear monotone equations. This method integrates the projection technique of Solodov and Svaiter with a new hybrid conjugate gradient parameter, which is defined as a convex combination of the RMIL (Rivaie et al.) and LS (Liu-Storey) conjugate gradient parameters. The search direction produced from this approach guarantees the adequate descent property. Under standard conditions, we prove the global convergence of the RMILLS-generated sequence. Evaluations on seven typical test instances, with scales reaching 10,000 to 100,000 variables, indicate that RMILLS surpasses HLSFR and HYBRIDSCG in efficiency and reliability, especially for large constrained systems. Additionally, we discuss its applicability in data-driven optimization.

• Publication year

  2025

• Venue

  2025 7th International Conference on Frontier Technologies of Information and Computer (ICFTIC)

• Publication date

  2025-12-05

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICFTIC68075.2025.11324754
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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