A Full Nesterov-Todd Step Infeasible Interior-point Method for Symmetric Optimization in the Wider Neighborhood of the Central Path

Details

• Alternative Title:
  Stat Optim Inf Comput
• Personal Author:
  Lesaja, G. ; Wang, G.Q. ; Oganian, A.
• Description:
  In this paper, an improved Interior-Point Method (IPM) for solving symmetric optimization problems is presented. Symmetric optimization (SO) problems are linear optimization problems over symmetric cones. In particular, the method can be efficiently applied to an important instance of SO, a Controlled Tabular Adjustment (CTA) problem which is a method used for Statistical Disclosure Limitation (SDL) of tabular data. The presented method is a full Nesterov-Todd step infeasible IPM for SO. The algorithm converges to |-approximate solution from any starting point whether feasible or infeasible. Each iteration consists of the feasibility step and several centering steps, however, the iterates are obtained in the wider neighborhood of the central path in comparison to the similar algorithms of this type which is the main improvement of the method. However, the currently best known iteration bound known for infeasible short-step methods is still achieved.
• Subjects:
  Article Control Tabular Adjustment Problem Euclidean Jordan Algebras Full Nesterov-Todd Step Interior-point Methods Linear Optimization Over Symmetric Cones Polynomial Complexity Statistical Disclosure Limitation Tabular Data
• Source:
  Stat Optim Inf Comput. 9(2):250-267
• Pubmed ID:
  34141814
• Pubmed Central ID:
  PMC8205320
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHSUnited States/
• Volume:
  9
• Issue:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:650c539227212dc5ff44ad1ef189891201f9d9036d79582df5641793da4f0fdf
• Download URL:
  https://stacks.cdc.gov/view/cdc/107363/cdc_107363_DS1.pdf
• File Type:
  [PDF - 736.19 KB ]