BMGT332 FINAL

A change in the value of an objective function coefficient will always change the value of the optimal solution.

False

A rounded down integer solution cannot result in a less than optimal solution to an integer programming model

False

A shortest path problem cannot be solved as an LP problem, but is solved easily using a simple manual algorithm.

False

If the objective function is parallel to a constraint, the constraint is infeasible.

False

If there are no feasible solutions to a linear programming model, then the best course of action for a manager is to choose a solution that violates at least one constraint.

False

In a simulation model, if the number of trials is greater than 1,000, the mean estimate of an output will be equal to the true population mean of the output.

False

Most computer linear programming packages readily accept constraints entered in fractional form, such as X1/X3.

False

Multiple optimal solutions occur when constraints are parallel to each other.

False

Nonlinear programming has the same format as linear programming, however either the objective function or the constraints (but not both) are nonlinear functions.

False

Sensitivity Analysis can be used to determine the effect on the solution for changing several parameters at once

False

The branch and bound solution method cannot be applied to 0-1 integer programming problems.

False

The optimal solution for a graphical linear programming problem is the corner point that is the farthest from the origin.

False

The sensitivity range for an objective function coefficient is the range of values over which the profit doesn't change

False

There is always exactly one optimal solution point to a linear program.

False

When solving a nonlinear program, the message "Solver found a solution. All constraints and optimality conditions are satisfied." means that a global optimal solution has been found for the problem.

False

What solving method is most generally used to solve nonlinear programs in Excel Solver?

GRG Non linear

Which of the following are assumptions or requirements of the transportation problem?

Goods are the same, regardless of source.

Which of the following is not a goal of spreadsheet design

Immutability

In a ______ linear programming model the solution values of the decision variables are whole numbers

Integer

In formulating a mixed integer programming problem, the constraint x1 + x2 ≤ 500y1 where y1 is a 0-1 variable, and x1 and x2 are continuous variables, then x1 + x2 = 500 if y1 is:

1

What characteristic best describes a degenerate solution?

A solution where an anomaly takes place

Which of the following statements is not true?

An infeasible solution violates all constraints.

In spreadsheet design, the ability to trace the steps followed to generate the different outputs from the model in order to understand the model and verify results is referred as

Auditability

Determine the worst payoff for each alternative and choosing the alternative with the best worst is called:

Maximin

What of the following situations does not require the LP problem to be revised?

Multiple optimal solution

In the Solver window, the cell that contains the objective function is referred as

Objective cell

The ________ command is used in generating the random numbers with Excel.

RAND()

Which of the following optimization tools is prepackaged with Excel?

Solver

What happens to the optimal solution (decision variables) when the RHS of a binding constraint increases within the allowable increase?

Some values in the optimal solution increase and others decrease.changes.

What happens to the objective function value when the RHS of a non binding constraint increases within the allowable increase?

The objective value stays the same.

What happens to the optimal solution (decision variables) when one of the coefficients in the objective function increases within the allowable increase?

The optimal solution does not change.

What statement best describes the shadow price?

The shadow price is the change in the objective function per unit change in the RHS of a constraint

"Solver found a solution. All constraints and optimality conditions are satisfied."

This means Solver found a local optimal solution, but does not guarantee that the solution is the global optimal solution.

"Solver has converged to the current solution. All constraints are satisfied."

This means the objective function value changed very slowly for the last few iterations.

1."Solver cannot improve the current solution. All constraints are satisfied."

This rare message means the your model is degenerate and the Solver is cycling. Degeneracy can often be eliminated by removing redundant constraints in a model.

A long period of real time can be represented by a short period of simulated time.

True

A minimum spanning tree problem cannot be solved as an LP problem, but is solved easily using a simple manual algorithm.

True

A payoff table is a means of organizing a decision situation, including the payoffs from different decisions given the various states of nature.

True

An assignment problem is a special form of transportation problems where all supply and demand values equal 1

True

Decision variables cannot be multiplied by each other in the objective function of a nonlinear program.

True

For most real-world applications, an unbalanced transportation model is a more likely occurrence than a balanced transportation model.

True

If we change the constraint quantity to a value outside the range of feasibility for that constraint quantity, the shadow price will change.

True

In a maximal flow problem, there is a unit supply at the origin and a unit supply at the destination.

True

In a mixed integer model, some solution values for decision variables are integer and others can be non-integer.

True

In a shortest path problem, there is a unit supply at the origin and a unit supply at the destination.

True

In an assignment problem all supply and demand values are equal to one.

True

In computer mathematical simulation, a system is replicated with a mathematical model that is analyzed with the computer.

True

LINDO is a specialized mathematical package that can solve extremely large optimization problems.

True

Linear programming is a model consisting of linear relationships representing a firm's decisions given an objective and resource constraints.

True

Manual simulation is limited because of the amount of real time required to simulate even one trial.

True

Modeling efforts should be directed towards the goal of communications, reliability, auditability and modifiability.

True

Monte Carlo is a technique for selecting numbers randomly from a probability distribution.

True

Nonlinear programming algorithms occasionally have difficulty distinguishing between local optima and the global optimum.

True

Rounding non-integer solution values up to the nearest integer value can result in an infeasible solution to an integer programming problem.

True

Sensitivity Analysis can be used to determine the effect of the solution for changing one parameter at. a time

True

The appropriate criterion is dependent on the risk personality and philosophy of the decision maker

True

The college dean is deciding among three equally qualified (in their eyes, at least) candidates for his associate dean position. If this situation could be modeled as an integer program, the decision variables would be cast as 0-1 integer variables.

True

The feasible solution area contains infinite solutions to the linear program.

True

The first step in formulating a linear programming model is to define the decision variables.

True

The graphical solution approach is limited to LP problems with just two decision variables; while appropriate computer software can solve almost any LP problem easily.

True

The highest point on each peak of a surface can be considered a local optimum, but the highest point among all of the peaks is the only global optimum.

True

The objective function always consists of either maximizing or minimizing some value.

True

The risk profile is an effective tool for breaking an expected monetary value into its component parts: possible outcomes and their chances.

True

The sensitivity range for a constraint quantity value is the range over which the shadow price is valid

True

There is exactly one optimal solution point to a linear program.

True

In order to determine the value of discrete demand in a simulation model using Excel, the ________ function is used to associate a specific value of demand with a random number.

VLOOKUP()

What is the term used by Solver to describe decision variables?

Variable cell

The shadow price of non-binding constraint is

Zero

A decision tree is a diagram consisting of

branches representing decision alternatives.

Both linear and nonlinear programming models are examples of:

constrained optimization models

A __ represents a limitation to achieving maximum profits due to limited resources

constraint

The _______________ is computed by multiplying each decision outcome under each state of nature by the probability of its occurrence.

expected value

In a transshipment problem, items may be transported

from destination to destination. from one transshipment point to another. directly from sources to destinations

In the linear programming formulation of a network flow problem,

here is one variable per arc the total flow in and out of a node is constrained by the supply or demand at the node there is one constraint per node

Unlike optimization models, simulation provides:

insights

The expected value of perfect information:

is the minimum expected opportunity loss

The minimax regret criterion:

minimizes the maximum regret

In a 0-1 integer programming model, if the constraint x1 - x2 = 0, it means when project 1 is selected, project 2 ________ be selected.

must also

If we are solving a 0-1 integer programming problem, the constraint x1 + x2 ≤ 1 is a ________ constraint.

mutually exclusive

The Lagrange multiplier reflects the appropriate change in the objective function for a unit change in the _______ of the constraint equation.

right hand side

People who forgo a high expected value to avoid a disaster with a low probability are:

risk averters

If a maximization linear programming problem consists of all less-than-or-equal-to constraints with all positive coefficients and the objective function consists of all positive objective function coefficients, then rounding down the linear programming optimal solution values of the decision variables will ________ result in a(n) ________ solution to the integer

sometimes,optimal

The appropriate criterion is dependent on

the risk personality of the decision maker

In the linear programming formulation of a network flow problem,

there is one variable per arc there is one constraint per node the total flow in and out of a node is constrained by the supply or demand at the node