新的无罚函数无滤子的序列二次规划方法

对一般的具有等式约束和不等式约束的非线性规划问题，提出了一个无罚函数无滤子的信赖域序列二次规划算法.整个算法分为两个阶段，第一阶段计算可行步，以达到减少约束违反度的目的，第二阶段为优化阶段，以减少目标函数的二次模型为目的.此算法中可行步和优化步是相对独立的，任何减少约束违反度的算法都可以应用，具有更大的灵活性.在合理的假设条件下，证明了算法的全局收敛性和局部收敛性.通过数值实验证实了算法的有效性.
A sequential quadratic programming method without using a penalty function or a filter was proposed. The algorithm computes the overall step in two phases. The first phase is to compute a feasibility step. The feasibility phase aims at reducing the infeasibility measure. The second phase, an optimality phase computes a trial point reducing a quadratic model of the objective function. The feasibility and optimality phases are independent in this algorithm; therefore, any method for reducing constraint violation can be used in the feasibility phase. Under mild conditions, the method can be proved to be globally convergent. Numerical results demonstrate the efficiency of this algorithm