Journal of Applied Mathematics

Constraint Consensus Methods for Finding Interior Feasible Points in Second-Order Cones

Anna Weigandt, Kaitlyn Tuthill, and Shafiu Jibrin

Full-text: Open access

Abstract

Optimization problems with second-order cone constraints (SOCs) can be solved efficiently by interior point methods. In order for some of these methods to get started or to converge faster, it is important to have an initial feasible point or near-feasible point. In this paper, we study and apply Chinneck's Original constraint consensus method and DBmax constraint consensus method to find near-feasible points for systems of SOCs. We also develop and implement a new backtracking-like line search technique on these methods that attempts to increase the length of the consensus vector, at each iteration, with the goal of finding interior feasible points. Our numerical results indicate that the new methods are effective in finding interior feasible points for SOCs.

Article information

Source
J. Appl. Math., Volume 2010 (2010), Article ID 307209, 19 pages.

Dates
First available in Project Euclid: 12 August 2011

Permanent link to this document
https://projecteuclid.org/euclid.jam/1313170329

Digital Object Identifier
doi:10.1155/2010/307209

Mathematical Reviews number (MathSciNet)
MR2764189

Zentralblatt MATH identifier
1208.90188

Citation

Weigandt, Anna; Tuthill, Kaitlyn; Jibrin, Shafiu. Constraint Consensus Methods for Finding Interior Feasible Points in Second-Order Cones. J. Appl. Math. 2010 (2010), Article ID 307209, 19 pages. doi:10.1155/2010/307209. https://projecteuclid.org/euclid.jam/1313170329


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