• AN SQP ALGORITHM OF LINEAR INEQUALITY CONSTRAINTS

Quanxiang Zhu, Zhijun Luo*, Mingjian Huan, Jianxue Luo

Abstract


In this paper, a kind of optimization problems with linear inequality constraints are discussed, and a sequential quadratic programming feasible descent algorithm for solving the problems is presented. In order to show the algorithm is well defined, we obtained a feasible descent direction by using generalized projection technique. The high-order revised direction which avoids Maratos effect is computed. Under some suitable conditions, the global and superlinear convergence can be obtained.

Keywords


linear inequality constraints; SQP method; Global convergence; superlinear convergence.

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