为在 filter-SQP (二次的编程的顺序) 证明集中全球的机制功能为抑制非线性的优化问题被描述的有非线性的补充问题(NCP ) 的方法。我们介绍 NCP 功能进过滤器并且构造一个新 SQP 过滤器算法。如此的方法被他们多客观的优化的优势概念的使用描绘,而不是其调整能有问题的一个惩罚参数。我们证明算法在一些温和条件下面有全球集中和超级线性集中率。
A mechanism for proving global convergence in filter-SQP (sequence of quadratic programming) method with the nonlinear complementarity problem (NCP) function is described for constrained nonlinear optimization problem.We introduce an NCP function into the filter and construct a new SQP-filter algorithm.Such methods are characterized by their use of the dominance concept of multi-objective optimization,instead of a penalty parameter whose adjustment can be problematic.We prove that the algorithm has global convergence and superlinear convergence rates under some mild conditions.