Remote Access Mathematics of Computation
Green Open Access

Mathematics of Computation

ISSN 1088-6842(online) ISSN 0025-5718(print)

Request Permissions   Purchase Content 
 

 

A perturbation approach for an inverse quadratic programming problem over second-order cones


Authors: Yi Zhang, Liwei Zhang, Jia Wu and Jianzhong Zhang
Journal: Math. Comp. 84 (2015), 209-236
MSC (2010): Primary 90C26, 90C33; Secondary 49M15, 49M20
DOI: https://doi.org/10.1090/S0025-5718-2014-02848-2
Published electronically: July 18, 2014
MathSciNet review: 3266958
Full-text PDF

Abstract | References | Similar Articles | Additional Information

Abstract: This paper is devoted to studying a type of inverse second-order cone quadratic programming problems, in which the parameters in both the objective function and the constraint set of a given second-order cone quadratic programming problem need to be adjusted as little as possible so that a known feasible solution becomes optimal. This inverse problem can be written as a minimization problem with second-order cone complementarity constraints and a positive semidefinite cone constraint. Applying the duality theory, we reformulate this problem as a linear second-order cone complementarity constrained optimization problem with a semismoothly differentiable objective function, which has fewer variables than the original one. A perturbed problem is proposed with the help of the projection operator over second-order cones, whose feasible set and optimal solution set are demonstrated to be continuous and outer semicontinuous, respectively, as the parameter decreases to zero. A smoothing Newton method is constructed to solve the perturbed problem and its global convergence and local quadratic convergence rate are shown. Finally, the numerical results are reported to show the effectiveness for the smoothing Newton method to solve the inverse second-order cone quadratic programming problem.


References [Enhancements On Off] (What's this?)


Similar Articles

Retrieve articles in Mathematics of Computation with MSC (2010): 90C26, 90C33, 49M15, 49M20

Retrieve articles in all journals with MSC (2010): 90C26, 90C33, 49M15, 49M20


Additional Information

Yi Zhang
Affiliation: Department of Mathematics, School of Science, East China University of Science and Technology, Shanghai, 200237, China.
Email: zhangyi8407@163.com

Liwei Zhang
Affiliation: School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China.
Email: lwzhang@dlut.edu.cn

Jia Wu
Affiliation: School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China.
Email: wujia@dlut.edu.cn

Jianzhong Zhang
Affiliation: Division of Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, 519085, China.
Email: jzzhang@uic.edu.hk

DOI: https://doi.org/10.1090/S0025-5718-2014-02848-2
Keywords: Inverse optimization, second-order cone quadratic programming, perturbation approach, smoothing Newton method.
Received by editor(s): March 18, 2011
Received by editor(s) in revised form: May 13, 2013
Published electronically: July 18, 2014
Additional Notes: The first author was supported by the Fundamental Research Funds for the Central Universities under project no. 222201314037 and the China Postdoctoral Science Foundation funded project no. 2013M541479
The second author was supported by the National Natural Science Foundation of China under project nos. 11071029, 91130007 and 91330206.
The third author was supported by the National Natural Science Foundation of China under project no. 11301049 and the China Postdoctoral Science Foundation funded project no. 2013M541217
Article copyright: © Copyright 2014 American Mathematical Society