Main

## Objective Variables

## Main.ObjectiveVariables History

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!! Objective Variables

Objective variables are defined to construct an objective function. The objective function is a summation of all variables that are designated as objective-type. Variables are defined as objective function contributions by starting with '''obj'''. Thus, the variables ''obj1'', ''objective'', ''object[1]'' would be included in the objective function summation.

Additionally, slack variables are included in the objective function. These variables begin with the key letters '''slk''' and are defined with a lower bound of zero.

!!! Minimize vs. Maximize

The objective function is always minimized with %blue%A%red%P%black%Monitor. Objective function maximization is accomplished by defining a new variable that is the negative of the minimized objective.

!!! Example

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(:cellnr:)

! Example model with an objective function

Model example

Parameters

p1 = 5

End Parameters

Variables

objective

v1 > 6

End Variables

Equations

objective = (v1 - p1)^2

End Equations

End Model

Solution

p1 = 5

v1 = 6

objective = 1

(:tableend:)

Objective variables are defined to construct an objective function. The objective function is a summation of all variables that are designated as objective-type. Variables are defined as objective function contributions by starting with '''obj'''. Thus, the variables ''obj1'', ''objective'', ''object[1]'' would be included in the objective function summation.

Additionally, slack variables are included in the objective function. These variables begin with the key letters '''slk''' and are defined with a lower bound of zero.

!!! Minimize vs. Maximize

The objective function is always minimized with %blue%A%red%P%black%Monitor. Objective function maximization is accomplished by defining a new variable that is the negative of the minimized objective.

!!! Example

(:table border=1 width=50% align=left bgcolor=#EEEEEE cellspacing=0:)

(:cellnr:)

! Example model with an objective function

Model example

Parameters

p1 = 5

End Parameters

Variables

objective

v1 > 6

End Variables

Equations

objective = (v1 - p1)^2

End Equations

End Model

Solution

p1 = 5

v1 = 6

objective = 1

(:tableend:)