A ROBUST SQP METHOD FOR OPTIMIZATION WITH INEQUALITY CONSTRAINTS

• 来源期刊: 计算数学（英文版）
• 关键词: nonlinear optimization SQP method global convergence superlinear conver-gence.
• 年，卷（期）: 2003,（2）
• 页码范围: 247-256
• 页数: 10页
• 语种: 英文

摘要

A new algorithm for inequality constrained optimization is presented, which solves a linear programming subproblem and a quadratic subproblem at each iteration. The algorithm can circumvent the difficulties associated with the possible inconsistency of QP subproblem of the original SQP method. Moreover, the algorithm can converge to a point which satisfies a certain first-order necessary condition even if the original problem is itself infeasible. Under certain condition, some global convergence results are proved and local superlinear convergence results are also obtained. Preliminary numerical results are reported.