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论文类型：期刊论文
发表时间：2013-01-01
发表刊物：JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
收录刊物：SCIE、Scopus
卷号：9
期号：1
页面范围：171-189
ISSN号：1547-5816
关键字：Inverse optimization; linear second-order cone programming; perturbation approach; damped Newton method
摘要：A type of inverse linear second-order cone programming problems is discussed, in which the parameters in both the objective function and the constraint set of a given linear second-order cone programming need to be adjusted as little as possible so that a known feasible solution becomes optimal. This inverse problem can be formulated as a minimization problem with second-order cone complementarity constraints. With the help of the smoothed Fischer-Burmeister function over second-order cones, we construct a smoothing approximation of the formulated problem whose feasible set and optimal solution set are demonstrated to be continuous and outer semicontinuous respectively at the perturbed parameter epsilon = 0. A damped Newton method is employed 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 of the damped Newton method for solving the inverse linear second-order cone programming.