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A full-NT-step infeasible interior-point algorithm for SDP based on kernel functions
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DOI：10.1016/j.amc.2010.11.049.png)
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Abstract
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This paper proposes an infeasible interior-point algorithm with full Nesterov-Todd (NT) steps for semidefinite programming (SDP). The main iteration consists of a feasibility step and several centrality steps. First we present a full NT step infeasible interior-point algorithm based on the classic logarithmical barrier function. After that a specific kernel function is introduced. The feasibility step is induced by this kernel function instead of the classic logarithmical barrier function. This kernel function has a finite value on the boundary. The result of polynomial complexity, O(n log n/epsilon), coincides with the best known one for infeasible interior-point methods. (c) 2010 Elsevier Inc. All rights reserved.
Keywords:
Semidefinite programming
Full Nesterov-Todd steps
Infeasible interior-point methods
Polynomial complexity
Kernel functions
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