Question 1

A traveling salesman problem with a starting city and 10 other cities that must be visited has 1,826,800 possible solutions.

Accepted Answer

A) True 
 B)False  False

Question 2

For a minimization problem being solved using a genetic algorithm,chromosomes that have a smaller fitness function have a lesser chance of surviving to the next generation.

Accepted Answer

A) True 
 B)False  False

Question 3

Exhibit 8-3
A gourmet snack company is seeking assistance with its pricing strategy.  Information about market size and customer sensitivity to price for the three market segments are provided below.
  
-Refer to Exhibit 8-4.Suppose Steve's company decides to locate a second salesperson in the region.Steve will now cover only Denver,Albuquerque,El Paso,Phoenix and Salt Lake City.The second salesperson will cover Los Angeles,San Diego,San Francisco,Portland,Seattle and Las Vegas.Formulate and solve shortest-path models for both salespersons.Is the total mileage for both salespersons more or less than in the case where Steve is the only salesperson

Accepted Answer

The shortest paths are shown below.The distance is more in this case (the extra distance is because both salespersons need to return home at the end of their routes).​     ​

Question 4

Evolutionary Solver works best when constraints are applied as:

Accepted Answer

A)  penalties 
B)  shortages 
C)  capacities 
D)  targets 
A)  penalties 
B)  shortages 
C)  capacities 
D)  targets

Question 5

For which of the following problems is the alldifferent constraint particularly useful

Accepted Answer

A)  nonlinear pricing 
B)  shortest path 
C)  estimating an S shaped relationship 
D)  portfolio optimization 
A)  nonlinear pricing 
B)  shortest path 
C)  estimating an S shaped relationship 
D)  portfolio optimization

Question 6

Genetic algorithms are not guaranteed to be fast,but they make up for it by being flexible.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following is not a step in a genetic algorithm

Accepted Answer

A)  Generating a population 
B)  Creating a new generation 
C)  Culling the population 
D)  Evaluating a stopping condition 
A)  Generating a population 
B)  Creating a new generation 
C)  Culling the population 
D)  Evaluating a stopping condition

Question 8

Exhibit 8-3
A gourmet snack company is seeking assistance with its pricing strategy.  Information about market size and customer sensitivity to price for the three market segments are provided below.
  
-Refer to Exhibit 8-3.Given that the unit cost of the gourmet snack is $2.50,use a single price model and evolutionary solver to determine the best unit price for them to charge.

Accepted Answer

Using Evolutionary S

Question 9

Exhibit 8-2
A television station has commercials of the following lengths (in seconds): 15, 20, 25, 30, 40, 45, 50, and 60. The commercials must be assigned to 90-second breaks. If a commercial break exceeds 90 seconds, a penalty cost is incurred. Station managers have established a penalty of $100 (per second) if the maximum limit is exceeded. Moreover, station owners want commercial breaks that are at least 65 seconds in duration. If any break fails to achieve this minimum duration, then a $1000 penalty (per occurrence) is charged.
-Refer to Exhibit 8-2.Explain why this problem typically requires Evolutionary Solver to obtain a solution.

Accepted Answer

There are different ways to formulate th

Question 10

Which of the following is not a form of non-linear pricing

Accepted Answer

A)  Two-part tariff 
B)  Surplus value 
C)  Selling only single item packs or packs of n items 
D)  Charging one price for the first n items and another price for the rest 
A)  Two-part tariff 
B)  Surplus value 
C)  Selling only single item packs or packs of n items 
D)  Charging one price for the first n items and another price for the rest

Question 11

In Evolutionary Solver,the initial population is chosen randomly,so the starting solution you enter in the changing cells is irrelevant.

Accepted Answer

A) True 
 B)False

Question 12

Exhibit 8-3
A gourmet snack company is seeking assistance with its pricing strategy.  Information about market size and customer sensitivity to price for the three market segments are provided below.
  
-Refer to Exhibit 8-4.Formulate and solve a shortest-path model using Evolutionary Solver.What is the shortest distance Steve can travel and visit all cities
 What is the route

Accepted Answer

The shortest path an

Question 13

Combinatorial problems have only a finite number of feasible solutions.

Accepted Answer

A) True 
 B)False

Question 14

The number of possible paths in a shortest path problem with n locations is:

Accepted Answer

A)  n 
B)  n − 1 
C)  n2 
D)  n! 
A)  n 
B)  n − 1 
C)  n2 
D)  n!

Question 15

The initial set of chromosomes generated by a genetic algorithm is called the population.

Accepted Answer

A) True 
 B)False

Question 16

The objective function in a genetic algorithm is called a:

Accepted Answer

A)  chromosome 
B)  fitness function 
C)  population 
D)  generation 
A)  chromosome 
B)  fitness function 
C)  population 
D)  generation

Question 17

The Evolutionary Solver setting that helps the algorithm explore a completely different area of the feasible region is:

Accepted Answer

A)  convergence 
B)  mutation rate 
C)  population size 
D)  random seed 
A)  convergence 
B)  mutation rate 
C)  population size 
D)  random seed

Question 18

Exhibit 8-3
A gourmet snack company is seeking assistance with its pricing strategy.  Information about market size and customer sensitivity to price for the three market segments are provided below.
  
-Refer to Exhibit 8-3.Due to a social media frenzy,the third customer segment now attaches more value to this gourmet snack. All of the prices it is willing to pay have increased by 20%. How does this change the recommended pricing strategy
​​

Accepted Answer

​ @#IMG-DLM& The fixed price has increas

Question 19

With two-part tariff pricing,it is assumed that a customer buys the quantity that provides the largest difference between value and total price.

Accepted Answer

A) True 
 B)False

Question 20

Mutations are useful for getting a genetic algorithm "unstuck".

Accepted Answer

A) True 
 B)False

A traveling salesman problem with a starting city and 10 other cities that must be visited has 1,826,800 possible solutions.

For a minimization problem being solved using a genetic algorithm,chromosomes that have a smaller fitness function have a lesser chance of surviving to the next generation.

Evolutionary Solver works best when constraints are applied as:

For which of the following problems is the alldifferent constraint particularly useful

Genetic algorithms are not guaranteed to be fast,but they make up for it by being flexible.

Which of the following is not a step in a genetic algorithm

Which of the following is not a form of non-linear pricing

In Evolutionary Solver,the initial population is chosen randomly,so the starting solution you enter in the changing cells is irrelevant.

Combinatorial problems have only a finite number of feasible solutions.

The number of possible paths in a shortest path problem with n locations is:

The initial set of chromosomes generated by a genetic algorithm is called the population.

The objective function in a genetic algorithm is called a:

The Evolutionary Solver setting that helps the algorithm explore a completely different area of the feasible region is:

With two-part tariff pricing,it is assumed that a customer buys the quantity that provides the largest difference between value and total price.

Mutations are useful for getting a genetic algorithm "unstuck".

Introduction to Modeling

Introduction to Spreadsheet Modeling

Introduction to Optimization Modeling

Linear Programming Models

Network Models

Optimization Models With Integer Variables

Nonlinear Optimization Models

Decision Making Under Uncertainty

Introduction to Simulation Modeling

Simulation Models

Queueing Models

Regression and Forecasting Models

Data Mining

Filters

Exam 8: Evolutionary Solver: An Alternative Optimization Procedure

A traveling salesman problem with a starting city and 10 other cities that must be visited has 1,826,800 possible solutions.

For a minimization problem being solved using a genetic algorithm,chromosomes that have a smaller fitness function have a lesser chance of surviving to the next generation.

Evolutionary Solver works best when constraints are applied as:

For which of the following problems is the alldifferent constraint particularly useful

Genetic algorithms are not guaranteed to be fast,but they make up for it by being flexible.

Which of the following is not a step in a genetic algorithm

Which of the following is not a form of non-linear pricing

In Evolutionary Solver,the initial population is chosen randomly,so the starting solution you enter in the changing cells is irrelevant.

Combinatorial problems have only a finite number of feasible solutions.

The number of possible paths in a shortest path problem with n locations is:

The initial set of chromosomes generated by a genetic algorithm is called the population.

The objective function in a genetic algorithm is called a:

The Evolutionary Solver setting that helps the algorithm explore a completely different area of the feasible region is:

With two-part tariff pricing,it is assumed that a customer buys the quantity that provides the largest difference between value and total price.

Mutations are useful for getting a genetic algorithm "unstuck".

Introduction to Modeling

Introduction to Spreadsheet Modeling

Introduction to Optimization Modeling

Linear Programming Models

Network Models

Optimization Models With Integer Variables

Nonlinear Optimization Models

Decision Making Under Uncertainty

Introduction to Simulation Modeling

Simulation Models

Queueing Models

Regression and Forecasting Models

Data Mining

Filters