The change in the optimal objective function value per unit increase in the right-hand side of a constraint is given by thea.objective function coefficient.b.shadow price.c.restrictive cost.d.allowable increase.In linear programming models of real problems, the occurrence of an unbounded solution means that thea.resultant values of the decision variables have no bounds.b.mathematical models sufficiently represent the real-world problems.c.problem formulation is improper.d.constraints have been excessively used in modeling.Which of the following error messages is displayed in Excel Solver when attempting to solve an unbounded problem?a.Solver could not find a feasible solution.b.Solver cannot improve the current solution. All constraints are satisfied.c.Solver could not find a bounded solution.d.Objective Cell values do not converge.The __________ assumption necessary for a linear programming model to be appropriate means that the contribution to the objective function and the amount of resources used in each constraint are in accordance to the value of each decision variable.a.proportionalityb.divisibilityc.additivityd.negativityA(n) ___________ solution satisfies all the constraint expressions simultaneously.a.feasibleb.objectivec.infeasibled.extremeGeometrically, binding constraints intersect to form thea.subspace.b.optimal point.c.decision cell.d.zero slack.The reduced cost for a decision variable that appears in a Sensitivity Report indicates the change in the optimal objective function value that results from changing the right-hand side of the nonnegativity constraint froma.1 to 0.b.0 to 1.c.-1 to 0.d.0 to -1.The points where constraints intersect on the boundary of the feasible region are termed as thea.feasible points.b.objective function contour.c.extreme points.d.feasible edges.Which algorithm, developed by George Dantzig and utilized by Excel Solver, is effective at investigating extreme points in an intelligent way to find the optimal solution to even very large linear programs?a.Ellipsoidal algorithmb.Complex algorithmc.Trial-and-error algorithmd.Simplex algorithmThe slack value for binding constraints isa.always a positive integer.b.zero.c.a negative integer.d.equal to the sum of the optimal points in the solution.The assumption that is necessary for a linear programming model to be appropriate and that ensures that the value of the objective function and the total resources used can be found by summing the objective function contribution and the resources used for all decision variables is known asa.proportionality.b.negativity.c.additivity.d.divisibility.A scenario in which the optimal objective function contour line coincides with one of the binding constraint lines on the boundary of the feasible region leads to __________ solutions.a.infeasibleb.alternative optimalc.bindingd.unique optimalA canned food manufacturer has its manufacturing plants in three locations across a state. Their product has to be transported to 3 central distribution centers, which in turn disperse the goods to 72 stores across the state. Which of the following visualization tools could help understand this problem better?a.Time-series plotb.Scatter chartc.Network graphd.Contour plotA(n) __________ refers to a set of points that yield a fixed value of the objective function.a.objective function coefficientb.infeasible solutionc.objective function contourd.feasible regionA variable subtracted from the left-hand side of a greater-than-or-equal to constraint to convert the constraint into an equality is known as a(n)a.surplus variable.b.slack variable.c.unbounded variable.d.binding constraint.When formulating a constraint, care must be taken to ensure thata.all the objective function coefficients are included.b.there are no inequalities in the mathematical expression.c.the decision variables are set at either maximum or minimum values.d.the units of measurement on both sides of the constraint match.The term __________ refers to the expression that defines the quantity to be maximized or minimized in a linear programming model.a.objective functionb.problem formulationc.decision variabled.association ruleA controllable input for a linear programming model is known as aa.parameter.b.decision variable.c.dummy variable.d.constraint.Constraints area.quantities to be maximized in a linear programming model.b.quantities to be minimized in a linear programming model.c.restrictions that limit the settings of the decision variables.d.input variables that can be controlled during optimization.Nonnegativity constraints ensure thata.the problem modeling includes only nonnegative values in the constraints.b.the solution to the problem will contain only nonnegative values for the decision variables.c.the objective function of the problem always returns maximum quantities.d.there are no inequalities in the constraints.
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