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摘要
In this paper, we present a sequential simple quadratically constrained quadratic programming (QCQP) norm-relaxed method for finely discretized semi-infinite optimization problems. At each iteration, the iteration point is feasible, and an improved search direction is solved by only one simple QCQP subproblem, in which only a few of constraints are chosen. Under some weak conditions, the proposed algorithm possesses weak global convergence. Finally, numerical results show that the proposed method is effective.
