Variable Constraints
Main.VariableConstraints History
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Variable constraints may lead to infeasible solutions. For square problems (n'_var_'=n'_eqn_'), the constraints are generally not needed but may help guide the solver to a feasible solution. Constraints are particularly advantageous to keep variable values away from strongly non-linear regions of the equation residuals. Good solvers correctly identify infeasible solutions and terminate.
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Variable constraints may lead to infeasible solutions. For square problems (n'_var_'=n'_eqn_'), the constraints are generally not needed but may help guide the solver to a feasible solution. Constraints are particularly advantageous to keep variable values away from strongly non-linear regions of the equation residuals. Good solvers correctly identify infeasible solutions and terminate with an appropriate message.
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!! Variable Constraints
Constraints serve to bound a parameter or variable with upper and lower limits. Variable constraints may be expressed as absolute numbers or functions of parameters or variable initial conditions. A variable constraint is included in the variable declarations section along with the initial condition. The constraints less than or equal (<=) or simply less than (<) are considered to be equivalent for numerical solutions. Likewise, greater than or equal (>=) and greater than (>) are equivalent.
!!! Infeasible Solution
Variable constraints may lead to infeasible solutions. For square problems (n'_var_'=n'_eqn_'), the constraints are generally not needed but may help guide the solver to a feasible solution. Constraints are particularly advantageous to keep variable values away from strongly non-linear regions of the equation residuals. Good solvers correctly identify infeasible solutions and terminate.
!!! Example
(:table border=1 width=50% align=left bgcolor=#EEEEEE cellspacing=0:)
(:cellnr:)
! Example model that demonstrates parameter declarations
Model example
Parameters
p1 = 1, >=0, < 2
p2 <= 5
End Parameters
Variables
v1 = 0, >-1, <1
v2 = 1, >=p1, <=p5*p1
End Variables
Equations
v1 * v2 = p2
v1 + v2 = p1
End Equations
End Model
(:tableend:)
Constraints serve to bound a parameter or variable with upper and lower limits. Variable constraints may be expressed as absolute numbers or functions of parameters or variable initial conditions. A variable constraint is included in the variable declarations section along with the initial condition. The constraints less than or equal (<=) or simply less than (<) are considered to be equivalent for numerical solutions. Likewise, greater than or equal (>=) and greater than (>) are equivalent.
!!! Infeasible Solution
Variable constraints may lead to infeasible solutions. For square problems (n'_var_'=n'_eqn_'), the constraints are generally not needed but may help guide the solver to a feasible solution. Constraints are particularly advantageous to keep variable values away from strongly non-linear regions of the equation residuals. Good solvers correctly identify infeasible solutions and terminate.
!!! Example
(:table border=1 width=50% align=left bgcolor=#EEEEEE cellspacing=0:)
(:cellnr:)
! Example model that demonstrates parameter declarations
Model example
Parameters
p1 = 1, >=0, < 2
p2 <= 5
End Parameters
Variables
v1 = 0, >-1, <1
v2 = 1, >=p1, <=p5*p1
End Variables
Equations
v1 * v2 = p2
v1 + v2 = p1
End Equations
End Model
(:tableend:)