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中文摘要：
讨论离散半无限规划问题,结合更新离散指标集的技术,提出一种新的可行序列二次规划（FSQP）算法求解由半无限规划（SIP）转化到离散半无限（DSI）问题,使得可行下降方向仅通过求解一个QP子问题可获得,为克服马太效应,高阶校正通过求解带有包含某个约束集的线性方程组所得。在适当的条件下,证明了算法的全局收敛性和超线性收敛性。
英文摘要：
A class of finely discretized semi-infinite programming （SIP） problems are discussed in this paper. In light of the technique of updating discretization index set, we present a new feasible sequential quadratic programming （FSQP）＇algorithm to solve the Discretized Semi-Infinite （DSI） problems from SIP. A feasible descention is obtained by solving only one QP sub-problem. In order to avoid Maratos effect, a high-order revised direction is computed by solving a linear system with involving some ＂active＂ constraints. The theoretical analysis shows that weak global and superlinear convergence can be deduced.
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