Deck 13: Introduction to Optimization Modeling
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Deck 13: Introduction to Optimization Modeling
1
Reduced costs indicate how much the objective coefficient of a decision variable that is currently 0 or at its upper bound must change before that the value of that variable changes.
True
2
It is instructive to look at a graphical solution procedure for LP models with three or more decision variables.
False
3
The proportionality property of LP models means that if the level of any activity is multiplied by a constant factor,then the contribution of this activity to the objective function,or to any of the constraints in which the activity is involved,is multiplied by the same factor.
True
4
In general,the complete solution of a linear programming problem involves three stages: formulating the model,invoking Solver to find the optimal solution,and performing sensitivity analysis.
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5
If an LP model does have an unbounded solution,then we must have made a mistake - either we made an input error or we omitted one or more constraints.
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6
Proportionality,additivity,and divisibility are three important properties that LP models possess,which distinguish them from general mathematical programming models:.
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7
There is often more than one objective in linear programming problems
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8
Suppose the allowable increase and decrease for shadow price for a constraint are $25 (increase)and $10 (decrease).If the right hand side of that constraint were to increase by $10 the optimal value of the objective function would change.
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9
If a constraint has the equation ,then the slope of the constraint line is function line is -2:
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10
When formulating a linear programming spreadsheet model,we specify the constraints in a Solver dialog box,since Excel does not show the constraints directly.
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11
Unboundedness refers to the situation in which the LP model has been formulated in such a way that the objective function is unbounded - that is,it can be made as large (for maximization problems)or as small (for minimization problems)as we like.
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12
All linear programming problems should have a unique solution,if they can be solved.
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13
All optimization problems include decision variables,an objective function,and constraints.
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14
When formulating a linear programming spreadsheet model,there is one target (objective)cell that contains the value of the objective function.
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15
In determining the optimal solution to a linear programming problem graphically,if the objective is to maximize the objective,we pull the objective function line down until it contacts the feasible region.
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16
Suppose the allowable increase and decrease for an objective coefficient of a decision variable that has a current value of $50 are $25 (increase)and $10 (decrease).If the coefficient were to change from $50 to $60,the optimal value of the objective function would not change.
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17
Linear programming problems can always be formulated algebraically,but not always on spreadsheet.
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18
If a solution to an LP problem satisfies all of the constraints,then is must be feasible.
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19
Shadow prices are associated with nonbinding constraints,and show the change in the optimal objective function value when the right side of the constraint equation changes by one unit.
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20
When formulating a linear programming spreadsheet model,there is a set of designated cells that play the role of the decision variables.These are called the objective cells.
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21
There are two primary ways to formulate a linear programming problem,the traditional algebraic way and in spreadsheets.
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22
Infeasibility refers to the situation in which there are no feasible solutions to the LP model
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23
In using Excel to solve linear programming problems,the target cell represents the:
A) value of the objective function
B) constraints
C) decision variables
D) total cost of the model
A) value of the objective function
B) constraints
C) decision variables
D) total cost of the model
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24
The feasible region in a graphical solution of a linear programming problem will appear as some type of polygon,with lines forming all sides.
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25
If a constraint has the equation ,then the constraint line passes through the points (0,20)and (30,0):
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26
The optimal solution to any linear programming model is a corner point of a polygon.
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27
When the proportionality property of LP models is violated,then we generally must use non-linear optimization.
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28
Nonbinding constraints will always have slack,which is the difference between the two sides of the inequality in the constraint equation.
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29
The feasible region in all linear programming problems is bounded by:
A) corner points
B) hyperplanes
C) an objective line
D) all of these options
A) corner points
B) hyperplanes
C) an objective line
D) all of these options
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30
The additivity property of LP models implies that the sum of the contributions from the various activities to a particular constraint equals the total contribution to that constraint.
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31
There are generally two steps in solving an optimization problem,model development and optimization.
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32
If the objective function has the equation ,then the y-intercept of the objective function line is 40:
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33
If the objective function has the equation ,then the slope of the objective function line is 2:
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34
The divisibility property of LP models simply means that we allow only integer levels of the activities.
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35
Consider the following linear programming problem:
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
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36
Suppose a firm must at least meet minimum expected demands of 60 for product x and 80 of product y.An algebraic formulation of these constraints is:
A)
B)
C)
D)
A)
B)
C)
D)
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37
It is often useful to perform sensitivity analysis to see how,or if,the optimal solution to a linear programming problem changes as we change one or more model inputs.
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38
The set of all values of the changing cells that satisfy all constraints,not including the nonnegativity constraints,is called the feasible region.
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39
It helps to ensure that Solver can find a solution to a linear programming problem if the model is well-scaled;that is,all of the numbers are of roughly the same magnitude.
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40
In an optimization model,there can only be one:
A) decision variable
B) constraint
C) objective function
D) shadow price
A) decision variable
B) constraint
C) objective function
D) shadow price
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41
When there is a problem with Solver being able to find a solution,many times it is an indication of a (n):
A) older version of Excel
B) nonlinear programming problem
C) problem that cannot be solved using linear programming
D) mistake in the formulation of the problem
A) older version of Excel
B) nonlinear programming problem
C) problem that cannot be solved using linear programming
D) mistake in the formulation of the problem
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42
Related to sensitivity analysis in linear programming,when the profit increases with a unit increase in a resource,this change in profit is referred to as the:
A) add-in price
B) sensitivity price
C) shadow price
D) additional profit
A) add-in price
B) sensitivity price
C) shadow price
D) additional profit
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43
The solution of a linear programming problem using Microsoft Excel typically involves the following three stages:
A) formulating the problem,invoking Solver,and sensitivity analysis
B) formulating the problem,graphing the problem,and sensitivity analysis
C) the changing cells,the target cells,and the constraints
D) the inputs,the changing cells,and the outputs
A) formulating the problem,invoking Solver,and sensitivity analysis
B) formulating the problem,graphing the problem,and sensitivity analysis
C) the changing cells,the target cells,and the constraints
D) the inputs,the changing cells,and the outputs
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44
The most important solution method for linear programming problems is known as the:
A) spreadsheet method
B) solution mix method
C) complex method
D) simplex method
A) spreadsheet method
B) solution mix method
C) complex method
D) simplex method
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45
Every linear programming problem involves optimizing a:
A) linear regression model subject to several linear constraints
B) linear function subject to several linear constraints
C) linear function subject to several non-linear constraints
D) non-linear function subject to several linear constraints
A) linear regression model subject to several linear constraints
B) linear function subject to several linear constraints
C) linear function subject to several non-linear constraints
D) non-linear function subject to several linear constraints
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46
The equation of the line representing the constraint
Passes through the points:
A)
B)
C)
D)
Passes through the points:
A)
B)
C)
D)
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47
In linear programming we can use the shadow price to calculate increases or decreases in:
A) binding constraints
B) nonbinding constraints
C) values of the decision variables
D) the value of the objective function
A) binding constraints
B) nonbinding constraints
C) values of the decision variables
D) the value of the objective function
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48
A linear programming problem with _____decision variable(s)can be solved by a graphical solution method.
A) 1
B) 2
C) 3
D) 4
A) 1
B) 2
C) 3
D) 4
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49
In most cases in solving linear programming problems,we want the decision variables to be:
A) equal to zero
B) nonnegative
C) nonpositive
D) All of these options
A) equal to zero
B) nonnegative
C) nonpositive
D) All of these options
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50
The equation of the line representing the constraint
Is:
A)
B)
C)
D)
Is:
A)
B)
C)
D)
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51
Suppose a liquor store sells beer for a net profit of $1 per unit and wine for a net profit of $2 per unit.Let x equal the amount of beer sold and y equal the amount of wine sold.An algebraic formulation of the profit function is:
A)
B)
C)
D)
A)
B)
C)
D)
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52
Linear programming is a subset of a larger class of models called:
A) mathematical programming models
B) mathematical optimality models
C) linear regression models
D) linear simplex model
A) mathematical programming models
B) mathematical optimality models
C) linear regression models
D) linear simplex model
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53
Consider the following linear programming problem:
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
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54
The additivity property of linear programming implies that the contribution of any decision variable to the objective is of/on the levels of the other decision variables.
A) dependent
B) independent
C) conditional
D) the sum
A) dependent
B) independent
C) conditional
D) the sum
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55
In using Excel to solve linear programming problems,the changing cells represent the:
A) value of the objective function
B) constraints
C) decision variables
D) total cost of the model
A) value of the objective function
B) constraints
C) decision variables
D) total cost of the model
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56
Consider the following linear programming problem:
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
Maximize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
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57
Suppose a company sells two different products,x and y,for net profits of $5 per unit and $10 per unit,respectively.The slope of the line representing the objective function is:
A) 0.5
B) -0.5
C) 2
D) -2
A) 0.5
B) -0.5
C) 2
D) -2
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58
In linear programming,sensitivity analysis involves examining how sensitive the optimal solution is to changes in:
A) profit of variables in model
B) cost of variables in model
C) resources available
D) All of these options
A) profit of variables in model
B) cost of variables in model
C) resources available
D) All of these options
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59
In some cases,a linear programming problem can be formulated such that the objective can become infinitely large (for a maximization problem)or infinitely small (for a minimization problem).This type of problem is said to be:
A) infeasible
B) inconsistent
C) unbounded
D) redundant
A) infeasible
B) inconsistent
C) unbounded
D) redundant
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60
The divisibility property of linear programming means that a solution can have both:
A) integer and noninteger levels of an activity
B) linear and nonlinear relationships
C) positive and negative values
D) revenue and cost information in the model
A) integer and noninteger levels of an activity
B) linear and nonlinear relationships
C) positive and negative values
D) revenue and cost information in the model
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61
Consider the following linear programming problem:
Minimize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
Minimize
Subject to
The above linear programming problem:
A) has only one optimal solution
B) has more than one optimal solution
C) exhibits infeasibility
D) exhibits unboundedness
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62
The prototype linear programming problem is to select an optimal mix of products to produce to maximize profit.This type of problem is referred to as the:
A) product mix problem
B) production problem
C) product/process problem
D) product scheduling problem
A) product mix problem
B) production problem
C) product/process problem
D) product scheduling problem
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63
When using the graphical solution method to solve linear programming problems,the set of points that satisfy all constraints is called the:
A) optimal region
B) feasible region
C) constrained region
D) logical region
A) optimal region
B) feasible region
C) constrained region
D) logical region
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64
All optimization problems have:
A) an objective function and decision variables
B) an objective function and constraints
C) decision variables and constraints
D) an objective function,decision variables and constraints
A company produces two products.Each product can be produced on either of two machines.The time (in hours)required to produce each product on each machine is shown below:
Machine 1
Machine 2
Product 1
5
4
Product 2
8
5
Each month,600 hours of time are available on each machine,and that customers are willing to buy up to the quantities of each product at the prices that are shown below:
Demands
Prices
Month 1
Month 2
Month 1
Month 2
Product 1
120
200
$60
$15
Product 2
150
130
$70
$35
The company's goal is to maximize the revenue obtained from selling units during the next two months.
A) an objective function and decision variables
B) an objective function and constraints
C) decision variables and constraints
D) an objective function,decision variables and constraints
A company produces two products.Each product can be produced on either of two machines.The time (in hours)required to produce each product on each machine is shown below:
Machine 1
Machine 2
Product 1
5
4
Product 2
8
5
Each month,600 hours of time are available on each machine,and that customers are willing to buy up to the quantities of each product at the prices that are shown below:
Demands
Prices
Month 1
Month 2
Month 1
Month 2
Product 1
120
200
$60
$15
Product 2
150
130
$70
$35
The company's goal is to maximize the revenue obtained from selling units during the next two months.
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65
Linear programming models have three important properties.They are:
A) optimality,additivity and sensitivity
B) optimality,linearity and divisibility
C) divisibility,linearity and nonnegativity
D) proportionality,additivity and divisibility
A) optimality,additivity and sensitivity
B) optimality,linearity and divisibility
C) divisibility,linearity and nonnegativity
D) proportionality,additivity and divisibility
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66
The term nonnegativity refers to the condition where:
A) the objective function cannot be less than zero
B) the decision variables cannot be less than zero
C) the right hand side of the constraints cannot be greater than zero
D) the reduced cost cannot be less than zero
A) the objective function cannot be less than zero
B) the decision variables cannot be less than zero
C) the right hand side of the constraints cannot be greater than zero
D) the reduced cost cannot be less than zero
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67
One of the things that you can do with linear programming and a spreadsheet model is to develop a user interface to make it easier for someone who is not an expert in using linear programming.The output can be a report that explains the optimal policy in non-technical terms.The type of system being described is called a (n):
A) expert system
B) decision support system
C) linear programming support system
D) production planning system
A) expert system
B) decision support system
C) linear programming support system
D) production planning system
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68
If a manufacturing process takes 3 hours per unit of x and 5 hours per unit of y and a maximum of 100 hours of manufacturing process time are available,then an algebraic formulation of this constraint is:
A)
B)
C)
D)
A)
B)
C)
D)
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69
The optimal solution to any linear programming model is:
A) the maximum objective function line
B) the minimum objective function line
C) the corner point of a polygon
D) the maximum or minimum of a parabola
A) the maximum objective function line
B) the minimum objective function line
C) the corner point of a polygon
D) the maximum or minimum of a parabola
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70
What are the decision variables in this problem?
Western Chassis produces high-quality polished steel and aluminum sheeting and two lines of industrial chassis for the rack mounting of Internet routers,modems,and other telecommunications equipment.The contribution margin (contribution toward profit)for steel sheeting is $0.40 per pound and for aluminum sheeting is $0.60 per pound.Western earns $12 contribution on the sale of a Standard chassis rack and $15 contribution on a Deluxe chassis rack.During the next production cycle,Western can buy and use up to 25,800 pounds of raw unfinished steel either in sheeting or in chassis.Similarly,20,400 pounds of aluminum are available.One standard chassis rack requires 16 pounds of steel and 8 pounds of aluminum.A Deluxe chassis rack requires 12 pounds of each metal.The output of metal sheeting is restricted only by the capacity of the polisher.For the next production cycle,the polisher can handle any mix of the two metals up to 4,000 pounds of metal sheeting.Chassis manufacture can be restricted by either metal stamping or assembly operations;no polishing is required.During the cycle no more than 2,500 total chassis can be stamped,and there will be 920 hours of assembly time available.The assembly time required is 24 minutes for the Standard chassis rack and 36 minutes for the Deluxe chassis rack.Finally,market conditions limit the number of Standard chassis racks sold to no more than 1,200 Standard and no more than 1,000 Deluxe.Any quantities of metal sheeting can be sold.
Western Chassis produces high-quality polished steel and aluminum sheeting and two lines of industrial chassis for the rack mounting of Internet routers,modems,and other telecommunications equipment.The contribution margin (contribution toward profit)for steel sheeting is $0.40 per pound and for aluminum sheeting is $0.60 per pound.Western earns $12 contribution on the sale of a Standard chassis rack and $15 contribution on a Deluxe chassis rack.During the next production cycle,Western can buy and use up to 25,800 pounds of raw unfinished steel either in sheeting or in chassis.Similarly,20,400 pounds of aluminum are available.One standard chassis rack requires 16 pounds of steel and 8 pounds of aluminum.A Deluxe chassis rack requires 12 pounds of each metal.The output of metal sheeting is restricted only by the capacity of the polisher.For the next production cycle,the polisher can handle any mix of the two metals up to 4,000 pounds of metal sheeting.Chassis manufacture can be restricted by either metal stamping or assembly operations;no polishing is required.During the cycle no more than 2,500 total chassis can be stamped,and there will be 920 hours of assembly time available.The assembly time required is 24 minutes for the Standard chassis rack and 36 minutes for the Deluxe chassis rack.Finally,market conditions limit the number of Standard chassis racks sold to no more than 1,200 Standard and no more than 1,000 Deluxe.Any quantities of metal sheeting can be sold.
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