An ODE-based nonmonotone method for unconstrained optimization problems

An ODE-based nonmonotone method for unconstrained optimization problems
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一种基于 ODE 的非单调无约束优化问题方法

DOI:
10.1007/s12190-012-0635-z
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发表时间:
2012-12
影响因子:
2.2
通讯作者:
Yuanyuan Liu
Yuanyuan Liu
中科院分区:
数学3区
文献类型:
--
作者:
Yigui Ou;Yuanyuan Liu

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将IMPBOT的思想与非单调技术相结合,提出了一种求解无约束优化问题的基于常微分方程的非单调方法。该方法的主要特点是在每次迭代中,通过改进的L-BFGS两循环递推算法,只需要向量内积,只需求解一次线性方程组,就可以得到一个试探步,从而减少了矩阵的计算量和存储量。然后用一种改进的非单调线搜索方法代替求解线性方程组来产生下一个迭代点。在一些合理的假设下,证明了该方法的全局收敛性和超线性收敛性。数值结果表明了该方法在实际计算中的有效性。
This paper proposes an ODE-based nonmonotone method for unconstrained optimization problems, which combines the idea of IMPBOT with the nonmonotone technique. The main characteristic of this method is that at each iteration, a system of linear equations is solved only once to obtain a trial step, via a modified L-BFGS two loop recursion that requires only vector inner products, thus reducing the matrix computation and storage. Then a modified nonmonotone line search is performed to generate next iterative point instead of resolving the linear system. Under some reasonable assumptions, the method is proven to be globally and superlinearly convergent. Numerical results show the efficiency of this proposed method in practical computation.
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