The global and superlinear convergence of a new nonmonotone MBFGS algorithm on convex objective functions |
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| Authors: | Liying Liu Shengwei Yao Zengxin Wei |
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| Affiliation: | aCollege of Mathematics Science, Liaocheng University, 252059, PR China;bCollege of Mathematics and Information Science, Guangxi University, 530004, PR China |
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| Abstract: | In this paper, a new nonmonotone MBFGS algorithm for unconstrained optimization will be proposed. Under some suitable assumptions, the global and superlinear convergence of the new nonmonotone MBFGS algorithm on convex objective functions will be established. Some numerical experiments show that this new nonmonotone MBFGS algorithm is competitive to the MBFGS algorithm and the nonmonotone BFGS algorithm. |
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| Keywords: | Nonmonotone linesearch MBFGS algorithm Global convergence Superlinear convergence Unconstrained optimization |
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