QA Module 3 Test

an objective function is necessary in a maximization problem but is not required in a minimization problem

False

any linear programming problem can be solved using the graphical solution procedure

False

in some instances, an infeasible solution may be the optimum found by the corner point method

False

one of the assumptions of LP is "proportionality"

True

resources restrictions are called constraints

True

the set of solution points that satisfies all of linear programming problems constraints simultaneously is defined as the feasible region in graphical linear programming

True

typical resources of an organization include

all of the above

a constraint with zero slack or surplus is called a

binding constraint

an LP formulation typically requires finding the maximum value of an objective whole simultaneously maximizing usage of the resource constraints

false

in a linear program, the constraints must be linear, but the objective function may be nonlinear

false

a feasible solution to a linear programming problem

must satisfy all of the problems constraints simultaneously

a constraint with positive sack or surplus is called a

nonbinding constraint

the difference between the left-hand side and the right-hand side of a less-than-or-equal-to constraint is referred to as

slack

sensitivity analysis enables us to look at the effects of changing the coefficients in the objective function, one at a time

true

the shadow price is the same as the dual price in maximization problems

true