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
Solution to 48 States Traveling Salesman Problem
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.
