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一种求解极大极小问题的灵活非单调滤子方法
A nonmonotone flexible filter method for minimax problems
【摘要】 求解极大极小问题的灵活非单调滤子方法与传统的滤子方法相比,对于试探步的可接受性,该方法具有更大的灵活性,而且与单调型方法相比,计算量更小.此外,还利用一个自适应参数来调整接受准则,从而在一定程度上避免了Maratos效应.在合理的假设下,该算法具有全局收敛性,并且通过数值实验验证了该方法的有效性.
【Abstract】 A nonmonotone flexible filter method for minimax problems is proposed.This new method has more flexibility for the acceptance of the trial step compared to the traditional filter methods,and requires less computational costs compared with the monotone-type methods.Moreover,we use a selfadaptive parameter to adjust the acceptance criteria,so that Maratos effect can be avoided to a certain degree.Under reasonable assumptions,the proposed algorithm is globally convergent.Numerical tests are presented that confirm the efficiency of the approach.
【关键词】 灵活滤子方法;
极大极小问题;
非单调;
信赖域;
全局收敛;
【Key words】 flexible filter method; minimax problem; nonmonotone; trust region; global convergence;
【Key words】 flexible filter method; minimax problem; nonmonotone; trust region; global convergence;
【基金】 河北省自然科学基金资助项目(A2018201172);河北省教育厅重点科研基金资助项目(ZD2015069);河北大学研究生创新项目(hbu2020ss043)
- 【文献出处】 河北大学学报(自然科学版) ,Journal of Hebei University(Natural Science Edition) , 编辑部邮箱 ,2020年06期
- 【分类号】O178
- 【下载频次】66