A polynomial time infeasible interior-point arc-search algorithm for convex optimization

Abstract

This paper proposes an infeasible interior-point algorithm for the convex optimization problem using arc-search techniques. The proposed algorithm simultaneously selects the centering parameter and the step size, aiming at optimizing the performance in every iteration. Analytic formulas for the arc-search are provided to make the arc-search method very efficient. The convergence of the algorithm is proved and a polynomial bound of the algorithm is established. The preliminary numerical test results indicate that the algorithm is efficient and effective.

arXiv comment29

References in corpus (5)

• An $\mathcal{O}(nL)$ Infeasible-Interior-Point Algorithm for Linear Programming
• Arc-Search Infeasible Interior-Point Algorithm for Linear Programming
• Two computationally efficient polynomial-iteration infeasible interior-point algorithms for linear programming
• An Efficient Polynomial Interior-Point Algorithm for Linear Programming
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Cited by in corpus (1)

• $\mathcal{N}$IPM-HLSP: An Efficient Interior-Point Method for Hierarchical Least-Squares Programs