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Polynomiality of an inexact infeasible interior point algorithm for semidefinite programming

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Abstract.

In this paper we present a primal-dual inexact infeasible interior-point algorithm for semidefinite programming problems (SDP). This algorithm allows the use of search directions that are calculated from the defining linear system with only moderate accuracy, and does not require feasibility to be maintained even if the initial iterate happened to be a feasible solution of the problem. Under a mild assumption on the inexactness, we show that the algorithm can find an ε-approximate solution of an SDP in O(n 2 ln(1/ε)) iterations. This bound of our algorithm is the same as that of the exact infeasible interior point algorithms proposed by Y. Zhang.

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Authors and Affiliations

  1. High Performance Computation for Engineered Systems, Singapore-MIT Alliance, 4 Engineering Drive 3, Singapore, 117576

    Guanglu Zhou

  2. Department of Mathematics, National University of Singapore, 2 Science Drive 2, Singapore, 117543

    Kim-Chuan Toh

Authors
  1. Guanglu Zhou
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  2. Kim-Chuan Toh
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Corresponding author

Correspondence to Guanglu Zhou.

Additional information

Research supported in part by the Singapore-MIT alliance, and NUS Academic Research Grant R-146-000-032-112.

Mathematics Subject Classification (1991): 90C05, 90C30, 65K05

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Zhou, G., Toh, KC. Polynomiality of an inexact infeasible interior point algorithm for semidefinite programming. Math. Program., Ser. A 99, 261–282 (2004). https://doi.org/10.1007/s10107-003-0431-5

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  • DOI: https://doi.org/10.1007/s10107-003-0431-5

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