A Novel Method for Unconstrained Multivariate Optimization Based on Fletcher Reeves Theory

doi:https://doi.org/10.1115/1.859926.paper58

A Novel Method for Unconstrained Multivariate Optimization Based on Fletcher Reeves Theory

Elías D. Niño,Luis Pacheco,M.B. Steer,Rafael Pérez‐Jiménez-2011-01-01-ASME Press eBooks

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TL;DRAbstract

There are some methods for optimization problems, they differ in the way the reach the optimum, among these methods, those which are based on the function's gradient have a great advantage as they find the fastest way to reach de objective, here we show three methods that base on this principle, two of them are part of our course, and a third one which we would like to propose, as it turns out to be very effective.

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There are some methods for optimization problems, they differ in the way the reach the optimum, among these methods, those which are based on the function's gradient have a great advantage as they find the fastest way to reach de objective, here we show three methods that base on this principle, two of them are part of our course, and a third one which we would like to propose, as it turns out to be very effective.

Keywords

Computer scienceMathematical optimizationMultivariate statisticsBase (topology)AlgorithmMathematicsMachine learning

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