## Objective Variables

## Main.ObjectiveVariables History

Show minor edits - Show changes to markup

This obtains the current objective function value. An objective may consist of multiple objectives that are maximized or minimized. They are all converted to minimization functions and added together.

This obtains the current objective function value with input arguments *s=server* and *a=application name*. An objective may consist of multiple objectives that are maximized or minimized. They are all converted to minimization functions and added together.

The APMonitor objective is reported in the minimized form. Thus, a maximized objective with a result of +17 is reported as -17. This is retrieved as the parameter *nlc.objfcnval* in a programming script from the *apm_tag* function such as:

The APMonitor objective is reported in the minimized form. Thus, a maximized objective with a result of +17 is reported as -17.

### Retrieve Objective Function

The objective function is retrieved as the parameter *nlc.objfcnval* in a programming script from the *apm_tag* function such as:

The objective function is always minimized with APMonitor. Objective function maximization is accomplished by defining a new variable that is the negative of the minimized objective.

The objective function is always minimized with APMonitor. Maximizing an objective function is accomplished by minimizing the negative of the original objective.

! original objective maximize z

The objective is modified by minimizing the negative of the original objective function.

! modified objective minimize -z

The APMonitor objective is reported in the minimized form. Thus, a maximized objective with a result of +17 is reported as -17. This is retrieved as the parameter *nlc.objfcnval* in a programming script from the *apm_tag* function such as:

obj = apm_tag(s,a,'nlc.objfcnval')

This obtains the current objective function value. An objective may consist of multiple objectives that are maximized or minimized. They are all converted to minimization functions and added together.

! 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

! Example model with an objective variable Parameters p1 = 5 Variables objective v1 > 6 Equations objective = (v1 - p1)^2

! Equivalent model with a minimize objective statement Parameters p1 = 5 Variables v1 > 6 Equations minimize (v1 - p1)^2

(:cellnr:)

! Equivalent model with a maximize objective statement Parameters p1 = 5 Variables v1 > 6 Equations maximize -(v1 - p1)^2

(:cellnr:)

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

(:table border=1 width=100% align=left bgcolor=#EEEEEE cellspacing=0:)

## 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 APMonitor. 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:)