# Difference between revisions of "Line search methods"

From optimization

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=Introduction= | =Introduction= | ||

− | + | An algorithm is a line search method if it seeks the minimum of a defined nonlinear function by selecting a reasonable direction vector that, when computed iteratively with a reasonable step size, will provide a function value closer to the absolute minimum of the function. Varying these will change the "tightness" of the optimization. For example, given the function <math>f(x)</math>, an initial <math>x</math> | |

+ | |||

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==Section 1.1== | ==Section 1.1== | ||

==Section 1.2== | ==Section 1.2== | ||

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=References= | =References= | ||

+ | 1. Sun, W. & Yuan, Y-X. (2006) Optimization Theory and Methods: Nonlinear Programming (Springer US) p 688. | ||

+ | |||

+ | 2. Anonymous (2014) Line Search. (Wikipedia). http://en.wikipedia.org/wiki/Line_search. |

## Revision as of 08:48, 24 May 2015

Author names: Elizabeth Conger

Steward: Dajun Yue and Fengqi You

## Contents |

# Introduction

An algorithm is a line search method if it seeks the minimum of a defined nonlinear function by selecting a reasonable direction vector that, when computed iteratively with a reasonable step size, will provide a function value closer to the absolute minimum of the function. Varying these will change the "tightness" of the optimization. For example, given the function , an initial

## Section 1.1

## Section 1.2

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# Section 2

# Section 3

# Conclusion

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# References

1. Sun, W. & Yuan, Y-X. (2006) Optimization Theory and Methods: Nonlinear Programming (Springer US) p 688.

2. Anonymous (2014) Line Search. (Wikipedia). http://en.wikipedia.org/wiki/Line_search.