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首页> 外文期刊>Results in mathematics >Global Convergence of Algorithms with Nonmonotone Line Search Strategy in Unconstrained Optimization
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Global Convergence of Algorithms with Nonmonotone Line Search Strategy in Unconstrained Optimization

机译:无约束优化中具有非单调线搜索策略的算法的全局收敛性

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摘要

In this paper we state some nonmonotone line search strategies for unconstrained optimization algorithms. Abstracting from the concrete line search strategy we prove two general convergence results. Using this theory we can show the global convergence of the BFGS method with nonmonotone line search strategy. In contrast to some former results about nonmonotone line search strategies, both our convergence results and their proofs are natural generalizations of known results for the monotone case.
机译:在本文中,我们针对无约束优化算法提出了一些非单调线搜索策略。从具体的线搜索策略中抽象出来,我们证明了两个一般的收敛结果。使用该理论,我们可以证明BFGS方法与非单调线搜索策略的全局收敛性。与以前有关非单调搜索策略的一些结果相反,我们的收敛结果及其证明都是单调情况下已知结果的自然概括。

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