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 self-adaptive 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.
SU Ke
,
LIN Yumeng
,
LI Xiaochuan
. A nonmonotone flexible filter method for minimax problems[J]. Journal of Hebei University(Natural Science Edition), 2020
, 40(6)
: 561
-568
.
DOI: 10.3969/j.issn.1000-1565.2020.06.001
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