Difference between revisions of "GoalSeek"

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= GoalSeek(Y,X,g) =
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Finds the value of ''X'' that makes variable ''Y'' equal to ''g''. 
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To use, X and Y should both be variables in your model.  GoalSeek solves a scalar problem.  The function can be used in an array abstracted fashion (for example, with an array of ''goals''), which amounts to solving several separate goal seek problems. 
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= Library =
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''Optimization Functions.ana''
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To use this function, use ''File --> Add Library...'' to embed (or link) the "Optimization Functions.ana" library in your model.
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= Comments =
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This is a simple Newton-Raphson-based algorithm for the scalar case.  GoalSeek can be used from any Analytica edition; however, the Analytica Optimizer edition allows more powerful and flexible "solving", which may be necessary if you need to deal with local optima or additional constraints. 
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An example of usage is included with the library.  The example finds the interest rate that achieves a desired bond value at maturity.
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= See Also =
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* [[NlpDefine]], [[QpDefine]], [[LpDefine]]
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* [[Solve]]

Revision as of 05:21, 15 July 2008


GoalSeek(Y,X,g)

Finds the value of X that makes variable Y equal to g.

To use, X and Y should both be variables in your model. GoalSeek solves a scalar problem. The function can be used in an array abstracted fashion (for example, with an array of goals), which amounts to solving several separate goal seek problems.

Library

Optimization Functions.ana

To use this function, use File --> Add Library... to embed (or link) the "Optimization Functions.ana" library in your model.

Comments

This is a simple Newton-Raphson-based algorithm for the scalar case. GoalSeek can be used from any Analytica edition; however, the Analytica Optimizer edition allows more powerful and flexible "solving", which may be necessary if you need to deal with local optima or additional constraints.

An example of usage is included with the library. The example finds the interest rate that achieves a desired bond value at maturity.

See Also

Comments


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