Abstract
Non monotone algorithms allow a possible increase of function values at certain iterations. This paper gives a suitable control on this increase to preserve the convergence properties of its monotone counterpart. A new efficient MultiLineal Search is also proposed for minimization algorithms.
Paper written with support of USB and Universidade de Vigo, Spain.
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Garcia-Palomares, U.M. (2006). Non Monotone Algorithms for Unconstrained Minimization: Upper Bounds on Function Values. In: Ceragioli, F., Dontchev, A., Futura, H., Marti, K., Pandolfi, L. (eds) System Modeling and Optimization. CSMO 2005. IFIP International Federation for Information Processing, vol 199. Springer, Boston, MA. https://doi.org/10.1007/0-387-33006-2_9
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DOI: https://doi.org/10.1007/0-387-33006-2_9
Publisher Name: Springer, Boston, MA
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