If the variable(s) in the constraint only have power 1 then it is linear. If any of the variables are squared, cubed, square rooted, etc, then it is non-linear.
what is 20 linear feet in quantity
Yes. If the feasible region has a [constraint] line that is parallel to the objective function.
what is 20 linear feet in quantity
Dealing with engineering or CAD, a geometric constraint deals with constraints such as parallel or perpendicularity. A numeric constraint deals with distances and size. Width, length, and depth are examples of these.--------Geometric constraints are constant, non-numerical relationships between the parts of a geometric figure. Numeric constraints are number values, or algebraic equations that are used to control the size or location of a geometric figure :)
Dealing with engineering or CAD, a geometric constraint deals with constraints such as parallel or perpendicularity. A numeric constraint deals with distances and size. Width, length, and depth are examples of these.--------Geometric constraints are constant, non-numerical relationships between the parts of a geometric figure. Numeric constraints are number values, or algebraic equations that are used to control the size or location of a geometric figure :)
Depends what you mean by the "size" of the figure.To double the linear dimensions of the figure ===> Multiply the linear dimensions by 2.To double the area of the figure ===> Multiply the linear dimensions by sqrt(2). (1.4142)
A linear programming question with two variables. Problems with three can be solved if there is a constraint that reduces them to effectively two variables. Linear programming with 3 variables, using 3-d graphs is possible but not recommended.
A figure has linear symmetry when after reflection, the image looks exactly the same as the original
62 linear inches is the same as a length of 62 inches. You don't need to figure, just get a measuring tape!
It is a non-numerical relationships between the parts of a geometric figure. Examples include parallelism, perpendicularity, and concentricity.
One. To be a (non-trivial) linear programming problem both the objective function and the constraints must be linear. If there were no constraints then the objective function could be made arbitrarily large or arbitrarily small. (Think of a line in two-space.) By adding one constraint the objective function's value can be limited to a finite value.
pi times the diameter