A trust region SQP-filter method for nonlinear second-order cone programming☆

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Abstract

In this paper, we consider the nonlinear second-order cone programming problem. By combining an SQP method and filter technique, we present a trust region SQP-filter method for solving this problem. The proposed algorithm avoids using the classical merit function with penalty term. Furthermore, under standard assumptions, we prove that the iterative sequence generated by the presented algorithm converges globally. Preliminary numerical results indicate that the algorithm is promising.

Keywords

Second-order cone programming
Sequence quadratic programming method
Filter technique
Trust region method
Global convergence

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This work is supported by the National Science Young Foundation of China (Grant No. 61100229) and the Fundamental Research Funds for the Central Universities under Grants No. K50510700005.

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