Chapter # 3 (Algorithm & Problem Solving)

A computational problem involves a set of step-by-step instructions that a computer can execute. This set of instructions is most commonly known as the:

• Input

• Process

• Output

• Algorithm

Which type of computational problem is defined by an output that is a simple "yes" or "no"?

• Optimization Problem

• Search Problem

• Decision Problem

• Counting Problem

What type of problem involves finding the best solution from a set of feasible solutions?

• Decision Problem

• Counting Problem

• Optimization Problem

• Search Problem

In which type of problem is the goal to enumerate all possible solutions?

• Optimization Problem

• Decision Problem

• Search Problem

• Counting Problem

The primary characteristic that distinguishes a Search Problem from other computational problems is that the task is to:

• Determine if the result is a simple "yes" or "no."

• Find a solution or an item that meets certain criteria.

• Count the number of ways certain conditions can be met.

• Determine the best possible outcome.

The problem of "finding the shortest route between two cities" is an example of which type of computational problem?

• Decision Problem (since the route exists or not)

• Counting Problem (since you count the stops)

• Optimization Problem (since "shortest" implies finding the best solution)

• Search Problem (since you are looking for a route)

A problem is considered well-defined if it has

• Vague and broad goals.

• Ambiguous inputs and requirements.

• Clear goals, inputs, processes, and outputs.

• Only one possible solution.

Which type of problem requires determining the number of ways to achieve a specific outcome?

• Decision Problem

• Counting Problem

• Optimization Problem

• Search Problem

In the Generate and Test Algorithm flowchart, what is the role of the TESTER component?

• To produce potential solutions to the problem.

• To determine if a potential solution meets the required conditions.

• To stop the process once a solution is found.

• To reduce the number of generated solutions.

The Generate and Test algorithm process continues until:

• The system runs out of memory

• An efficient heuristic is found.

• The generated solution is found to be incorrect.

• A satisfactory solution is found or all possible solutions have been exhausted.