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Note on the Second-Order Convergence of Optimization Algorithms Using BarrierFunctions

机译:关于使用BarrierFunction的优化算法的二阶收敛性的注记

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It has long been known that barrier algorithms for constrained optimization canproduce a sequence of iterates converging to a critical point satisfying weak second-order necessary optimality conditions, when their inner iterations ensures that second-order necessary conditions hold at each barrier minimizer. The authors show that, despite this, strong second-order necessary conditions may fail to be attained at the limit, even if the barrier minimizers satisfy second-order sufficient optimality conditions.

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