A Wide Neighborhood Second-order Predictor-corrector Interior-point Algorithm for Semidefinite Optimization with Modified Corrector Directions

2017 ◽  
Vol 153 (4) ◽  
pp. 327-346 ◽  
Author(s):  
Behrouz Kheirfam ◽  
Mohaddeseh Mohamadi-Sangachin
Keyword(s):  
Interior Point ◽  
Second Order ◽  
Semidefinite Optimization ◽  
Interior Point Algorithm ◽  
Wide Neighborhood ◽  
Predictor Corrector

A Wide Neighborhood Interior-Point Algorithm for Convex Quadratic Semidefinite Optimization

2018 ◽  
Vol 8 (1) ◽  
pp. 145-164
Author(s):  
Mohammad Pirhaji ◽  
Maryam Zangiabadi ◽  
Hossien Mansouri ◽  
Ali Nakhaei ◽  
Ali Shojaeifard
Keyword(s):  
Interior Point ◽  
Semidefinite Optimization ◽  
Interior Point Algorithm ◽  
Wide Neighborhood

scholarly journals A new second-order corrector interior-point algorithm for P*(k)-LCP

Filomat ◽  
2017 ◽  
Vol 31 (20) ◽  
pp. 6379-6391 ◽  
Author(s):  
B. Kheirfam ◽  
M. Chitsaz
Keyword(s):  
Interior Point ◽  
Complementarity Problems ◽  
Linear Complementarity Problems ◽  
Linear Complementarity ◽  
Second Order ◽  
Interior Point Algorithm ◽  
Iteration Complexity ◽  
Improve Performance ◽  
Complexity Bound ◽  
Wide Neighborhood

In this paper, we propose a second-order corrector interior-point algorithm for solving P*(k)- linear complementarity problems. The method generates a sequence of iterates in a wide neighborhood of the central path introduced by Ai and Zhang. In each iteration, the method computes a corrector direction in addition to the Ai-Zhang direction, in an attempt to improve performance. The algorithm does not depend on the handicap k of the problem, so that it can be used for any P*(k)-linear complementarity problems. It is shown that the iteration complexity bound of the algorithm is O ((1+k)3 ? nL). Some numerical results are provided to illustrate the performance of the algorithm.

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