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Variant Gradient Projection Methods for the Minimization Problems

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  • Yonghong Yao
  • Yeong-Cheng Liou
  • Ching-Feng Wen

Abstract

The gradient projection algorithm plays an important role in solving constrained convex minimization problems. In general, the gradient projection algorithm has only weak convergence in infinite-dimensional Hilbert spaces. Recently, H. K. Xu (2011) provided two modified gradient projection algorithms which have strong convergence. Motivated by Xu’s work, in the present paper, we suggest three more simpler variant gradient projection methods so that strong convergence is guaranteed.

Suggested Citation

  • Yonghong Yao & Yeong-Cheng Liou & Ching-Feng Wen, 2012. "Variant Gradient Projection Methods for the Minimization Problems," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-16, July.
    • Handle: RePEc:hin:jnlaaa:792078
    DOI: 10.1155/2012/792078
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