A SURVEY OF NUMERICAL METHODS FOR NONLINEAR SEMIDEFINITE PROGRAMMING

• Yamashita Hiroshi

  NTT DATA Mathematical Systems Inc.

• Yabe Hiroshi

  Tokyo University of Science

抄録

Nonlinear semidefinite programming (SDP) problems have received a lot of attentions because of large variety of applications. In this paper, we survey numerical methods for solving nonlinear SDP problems. Three kinds of typical numerical methods are described; augmented Lagrangian methods, sequential SDP methods and primal-dual interior point methods. We describe their typical algorithmic forms and discuss their global and local convergence properties which include rate of convergence.

収録刊行物

• 日本オペレーションズ・リサーチ学会論文誌

  日本オペレーションズ・リサーチ学会論文誌 58 (1), 24-60, 2015

  公益社団法人 日本オペレーションズ・リサーチ学会

キーワード

• Optimization
• nonlinear semidefinite programming
• augmented Lagrangian method
• sequential SDP method
• primal-dual interior point method

詳細情報

• CRID: 1390001204109260800
• NII論文ID: 130005067216
• NII書誌ID: AA00703935
• DOI: 10.15807/jorsj.58.24
• ISSN: 21888299
• ISSN: 04534514
• NDL書誌ID: 026225850
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I026225850
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可