Geodesic
A new three-term conjugate gradient method for solving the finite minimax problems
Filomat, Tome 35 (2021) no. 3, p. 737

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DOI

In this paper, we consider the method for solving the finite minimax problems. By using the exponential penalty function to smooth the finite minimax problems, a new three-term nonlinear conjugate gradient method is proposed for solving the finite minimax problems, which generates sufficient descent direction at each iteration. Under standard assumptions, the global convergence of the proposed new three-term nonlinear conjugate gradient method with Armijo-type line search is established. Numerical results are given to illustrate that the proposed method can efficiently solve several kinds of optimization problems, including the finite minimax problem, the finite minimax problem with tensor structure, the constrained optimization problem and the constrained optimization problem with tensor structure
DOI : 10.2298/FIL2103737H
Classification : 90C47, 90C30, 15A69
Keywords: finite minimax problem, tensor structure, three-term nonlinear conjugate gradient method, global convergence, polynomial complementarity problem 
Yue Hao; Shouqiang Du; Yuanyuan Chen. A new three-term conjugate gradient method for solving the finite minimax problems. Filomat, Tome 35 (2021) no. 3, p. 737 . doi: 10.2298/FIL2103737H
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     author = {Yue Hao and Shouqiang Du and Yuanyuan Chen},
     title = {A new three-term conjugate gradient method for solving the finite minimax problems},
     journal = {Filomat},
     pages = {737 },
     year = {2021},
     volume = {35},
     number = {3},
     doi = {10.2298/FIL2103737H},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2103737H/}
}
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