Genetic Algorithm Quiz
A genetic algorithm is a way of solving some optimization problems doesn’t matter if they are constrained or unconstrained. It is derived from Charles Darwin biological evolution theory. It is important for one to get a proper hold of this algorithm when it comes to data mining. Do you think you do? Take up the quick true or false quiz below and get to test your understanding of the genetic algorithm. Good luck!
- 1.In the choice phase of problem solving, normative models involve selecting an optimal or best outcome
- A.
True
- B.
False
- 2.Analytical techniques for problem solving are best for unstructured rather than structured problems.
- A.
True
- B.
False
- 3.Heuristic approaches are typically used to solve more complex problems.
- A.
True
- B.
False
- 4.Genetic algorithms are heuristic methods that do not guarantee an optimal solution to a problem
- A.
True
- B.
False
- 5.A "what-if" model is most typically used for the most structured problems
- A.
True
- B.
False
- 6.The use of simulation models is desirable because they can usually be solved in one pass, without incurring the time and cost of iterations
- A.
True
- B.
False
- 7.An advantage of simulation is that it allows model builders to solve problems with minimal interaction with users or managers
- A.
True
- B.
False
- 8.Time compression in a simulation allows managers to test certain strategies with less risk.
- A.
True
- B.
False
- 9.Simulation solutions cannot easily be transferred from one problem domain to another
- A.
True
- B.
False
- 10.Determining the duration of the simulation occurs before the model is validated and teste
- A.
True
- B.
False
- 11.Discrete events and agent-based models are usually used for middle or low levels of abstraction
- A.
True
- B.
False
- 12.. In steady-state plant control design, time-independent simulation would be appropriate
- A.
True
- B.
False
- 13.Simulation does not usually allow decision makers to see how a solution to a complex problem evolves over (compressed) time, nor can decision makers interact with the simulation
- A.
True
- B.
False
- 14.Visual interactive simulation (VIS) is a simulation method that lets decision makers see what the model is doing and how it interacts with the decisions made, as they are made
- A.
True
- B.
False
- 15.Visual interactive modeling (VIM) systems, especially those developed for the military and the video-game industry, have "thinking" characters who can behave with a relatively high level of intelligence in their interactions with users
- A.
True
- B.
False
- 16.How does blind search differ from optimization
- A.
) Blind search cannot result in optimal solutions whereas optimization methods do
- B.
Blind search represents a guided approach while optimization is unguided
- C.
Blind search usually does not conclude in one step like some optimization methods.
- D.
Blind search is usually a more efficient problem solving approach than optimization
- 17.In modeling, an optimal solution is understood to be
- A.
a solution that can only be determined by an exhaustive enumeration and testing of alternatives.
- B.
a solution found in the least possible time and using the least possible computing resources
- C.
A solution that is the best based on criteria defined in the design phase
- D.
a solution that requires an algorithm for determination.
- 18.When is a complete enumeration of solutions used?
- A.
When a solution that is "good enough" is fine and good heuristics are available
- B.
when there is enough time and computational power available
- C.
when the modeler requires a guided approach to problem solving
- D.
when there are an infinite number of solutions to be searched
- 19.All of the following are true about heuristics EXCEPT
- A.
heuristics are used when the modeler requires a guided approach to problem solving
- B.
) heuristics are used when a solution that is "good enough" is sought
- C.
heuristics are used when there is abundant time and computational power
- D.
Heuristics are rules of good judgment.
- 20.Which approach is most suited to structured problems with little uncertainty)
- A.
simulation
- B.
human intuition
- C.
Optimization
- D.
genetic algorithms
- 21.. Genetic algorithms belong to the family of methods in the
- A.
artificial intelligence area.
- B.
optimization area.
- C.
complete enumeration family of methods
- D.
Non-computer based (human) solutions area
- 22.All of the following are suitable problems for genetic algorithms EXCEPT
- A.
dynamic process control
- B.
pattern recognition with complex patterns
- C.
simulation of biological models
- D.
simple optimization with few variables
- 23.Which approach is most suited to complex problems with significant uncertainty, a need for experimentation, and time compression?
- A.
simulation
- B.
optimization
- C.
human intuition
- D.
genetic algorithms
- 24.Which of the following is an advantage of simulation?
- A.
It can incorporate significant real-life complexity
- B.
It always results in optimal solutions.
- C.
Simulation software requires special skills.
- D.
It solves problems in one pass with no iterations
- 25.In which stage of the simulation methodology do you determine the variables and gather data
- A.
Defining the problem
- B.
constructing the simulation model
- C.
testing and validating the model
- D.
designing the experiment
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