Operations Management Study Set 5

Linear programming techniques will always produce an optimal solution to an LP problem.

A maximization problem is limited by all greater than or equal to constraints.

The equation 3 xy = 9 is linear.

The term range of feasibility refers to a constraint's right-hand-side quantity.

Constraints limit the alternatives available to a decision maker

The simplex method is a general-purpose LP algorithm that can be used for solving only problems with more than six variables.

Profit maximization could be an objective of an LP problem; but cost minimization cannot be the objective of an LP problem.

The feasible solution space only contains points that satisfy all constraints.

An objective function represents a family of parallel lines.

The term range of feasibility refers to coefficients of the objective function.

If a single optimal solution exists to a graphical LP problem, it will exist at a corner point.

The value of an objective function always decreases as it is moved away from the origin.

The equation 5 x + 7 y = 10 is linear.

A linear programming problem can have multiple optimal solutions.

The term isoprofit line means that all points on the line will yield the same profit.

LP problems must have a single goal or objective specified.

The feasible solution space is the set of all feasible combinations of decision variables as defined by only binding constraints.

Graphical linear programming can handle problems that involve any number of decision variables.

A change in the value of an objective function coefficient does not change the optimal solution.

A shadow price indicates how much a one-unit decrease/increase in the right-hand-side value of a constraint will decrease/increase the optimal value of the objective function.