Ch. 10 - Modeling and Analysis: Heuristic Search Methods and Simulation Flashcards
In the choice phase of problem solving, normative models involve selecting an optimal or best outcome.
True
Analytical techniques for problem solving are best for unstructured rather than structured problems.
False
Heuristic approaches are typically used to solve more complex problems.
True
Genetic algorithms are heuristic methods that do not guarantee an optimal solution to a problem.
True
A “what-if” model is most typically used for the most structured problems.
False
The use of simulation models is desirable because they can usually be solved in one pass, without incurring the time and cost of iterations.
False
An advantage of simulation is that it allows model builders to solve problems with minimal interaction with users or managers.
False
Time compression in a simulation allows managers to test certain strategies with less risk.
True
Simulation solutions cannot easily be transferred from one problem domain to another.
True
Determining the duration of the simulation occurs before the model is validated and tested.
False
Discrete events and agent-based models are usually used for middle or low levels of abstraction.
True
In steady-state plant control design, time-independent simulation would be appropriate.
True
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.
True
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.
True
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.
True
How does blind search differ from optimization?
A) Blind search cannot result in optimal solutions whereas optimization methods do.
B) Blind search usually does not conclude in one step like some optimization methods.
C) Blind search is usually a more efficient problem solving approach than optimization.
D) Blind search represents a guided approach while optimization is unguided.
B) Blind search usually does not conclude in one step like some optimization methods.
In modeling, an optimal solution is understood to be
A) a solution found in the least possible time and using the least possible computing resources.
B) a solution that can only be determined by an exhaustive enumeration and testing of alternatives.
C) a solution that is the best based on criteria defined in the design phase.
D) a solution that requires an algorithm for determination.
C) a solution that is the best based on criteria defined in the design phase.
When is a complete enumeration of solutions used?
A) when there are an infinite number of solutions to be searched
B) when the modeler requires a guided approach to problem solving
C) when a solution that is “good enough” is fine and good heuristics are available
D) when there is enough time and computational power available
D) when there is enough time and computational power available
All of the following are true about heuristics EXCEPT
A) heuristics are rules of good judgment.
B) heuristics are used when the modeler requires a guided approach to problem solving.
C) heuristics are used when a solution that is “good enough” is sought.
D) heuristics are used when there is abundant time and computational power.
D) heuristics are used when there is abundant time and computational power.
Which approach is most suited to structured problems with little uncertainty?
A) simulation
B) genetic algorithms
C) optimization
D) human intuition
C) optimization
Genetic algorithms belong to the family of methods in the
A) optimization area.
B) complete enumeration family of methods.
C) artificial intelligence area.
D) non-computer based (human) solutions area.
C) artificial intelligence area.
All of the following are suitable problems for genetic algorithms EXCEPT
A) dynamic process control.
B) simulation of biological models.
C) pattern recognition with complex patterns.
D) simple optimization with few variables.
D) simple optimization with few variables.
Which approach is most suited to complex problems with significant uncertainty, a need for experimentation, and time compression?
A) simulation
B) genetic algorithms
C) optimization
D) human intuition
A) simulation
Which of the following is an advantage of simulation?
A) It always results in optimal solutions.
B) It can incorporate significant real-life complexity.
C) It solves problems in one pass with no iterations.
D) Simulation software requires special skills.
B) It can incorporate significant real-life complexity.