greedy algorithm

Greedy Algorithm Introduction A greedy algorithm is a problem-solving approach that makes a series of choices, each of which looks the best at the moment, with the hope that these local optimal choices will lead to a global optimum. This technique is significant in algorithm design, particularly in optimization problems, where the goal is to find the most efficient solution with minimal compu...

Quiz Type

Practice

Subject

Computer Science

Level

Level 600

Questions

20 questions

Created By

Akotia Louis

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Time limit: 20 minutes
Multiple attempts are not allowed
All questions must be answered to submit

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Question 1 of 20

Question 1

Multiple choice

Which of the following is NOT a characteristic of greedy algorithms?

Efficiency in achieving a solution.

Always producing the optimal solution.

Correct

Making decisions based on current circumstances.

Building solutions incrementally.

Explanation

While greedy algorithms are efficient and incrementally build solutions, they do not always produce the optimal solution for every problem.

Question 2

Multiple choice

Which algorithmic property suggests that only certain problems should be solved with greedy methods?

Greedy Choice Property

Optimal Substructure

Suitability Condition

Correct

Complexity Condition

Explanation

Not all problems are suited for greedy algorithms; those that are demonstrate both the greedy choice property and optimal substructure.

Question 3

Multiple choice

What type of problems do greedy algorithms most efficiently solve?

Problems with dynamic programming solutions only.

Problems that do not require an optimal solution.

Optimization problems where local choices lead to global benefits.

Correct

Problems where brute-force solutions are always available.

Explanation

Greedy algorithms are particularly effective in optimization problems where local optimum choices can lead toward global optimum results.

Question 4

Multiple choice

What is a greedy algorithm primarily used for?

Finding the maximum solution regardless of efficiency.

Solving every type of problem with the same approach.

Making a series of local optimal choices to reach a global optimum.

Correct

Optimizing problems using complex calculations and iterations.

Explanation

A greedy algorithm makes a series of choices that seem best at the moment, aiming for a global optimum through local optimums.

Question 5

Multiple choice

Which property indicates that a globally optimal solution can be reached by choosing local optimal solutions?

Optimal Substructure

Greedy Choice Property

Correct

Non-Optimal Solution

Complete Backtracking

Explanation

The Greedy Choice Property asserts that making local optimum choices can lead to a globally optimal solution.

Question 6

Multiple choice

Which of the following algorithms is an example of a greedy algorithm used in graph theory?

Dijkstra's Algorithm

A* Search Algorithm

Prim's Algorithm

Correct

Depth-First Search

Explanation

Prim's Algorithm is a greedy algorithm used to find minimum spanning trees in graph theory.

Question 7

Multiple choice

In the context of greedy algorithms, what does 'optimal substructure' mean?

The problem cannot be broken down into smaller problems.

Optimal solutions to subproblems contribute to the overall solution.

Correct

Only one solution exists for each problem.

Subproblems are irrelevant to the main problem.

Explanation

Optimal substructure indicates that an optimal solution for the entire problem can be constructed efficiently from optimal solutions of its subproblems.

Question 8

Multiple choice

Which problem does the greedy algorithm address when it aims to minimize the number of coins used for change?

Job Scheduling Problem

Traveling Salesman Problem

Coin Change Problem

Correct

Knapsack Problem

Explanation

The Coin Change Problem is a classic example of a problem solved using a greedy algorithm to minimize the number of coins needed.

Question 9

Multiple choice

What is the primary method used in the greedy coin change algorithm presented in the notes?

Selecting the smallest denomination first.

Using dynamic programming to find all combinations.

Choosing the largest denomination first.

Correct

Random selection of coins.

Explanation

The greedy coin change algorithm selects the largest denomination first to ensure the fewest coins are used in making change.

Question 10

Multiple choice

In the activity selection problem, what criteria does the greedy algorithm use for selecting activities?

Choosing activities based on the longest duration.

Selecting activities randomly.

Selecting activities based on their finish times.

Correct

Choosing based on the earliest start time.

Explanation

The greedy algorithm in the activity selection problem selects activities based on their finish times to maximize the number of non-overlapping activities.

Question 11

Multiple choice

In which scenario would a greedy algorithm likely fail to find an optimal solution?

Graph problems with a defined structure.

Problems requiring a combination of elements.

Correct

Resource allocation with simple constraints.

Pathfinding in well-defined areas.

Explanation

Greedy algorithms can fail when the problem requires exploring combinations or when local optimal choices can lead to a suboptimal overall solution.

Question 12

Multiple choice

Which of the following best describes the greedy method in algorithm design?

An exhaustive approach evaluating all possibilities.

A method that breaks problems into smaller independent parts.

A technique that focuses on immediate benefits without revisiting decisions.

Correct

A random approach that selects options arbitrarily.

Explanation

The greedy method emphasizes selecting the best immediate choice at each step, foregoing the need to evaluate past choices.

Question 13

Multiple choice

Which of the following is an application of greedy algorithms in coding theory?

Quick Sort

Huffman coding for data compression

Correct

Graph coloring algorithms

Breadth-First Search

Explanation

Huffman coding is a greedy algorithm used in coding theory to create optimal binary trees based on frequency of occurrences.

Question 14

Multiple choice

What is the primary goal of the activity selection problem?

Minimize overlapping activities.

Correct

Maximize the time spent in activities.

Choose the least number of activities.

Select activities based on popularity.

Explanation

The activity selection problem aims to maximize the number of chosen activities that do not overlap in time.

Question 15

Multiple choice

What is a key limitation of greedy algorithms?

They always offer a unique solution.

They can be computationally expensive in every case.

They often do not consider the global context of problems.

Correct

They require comprehensive algorithms to be viable.

Explanation

Greedy algorithms may miss the global context of a problem by focusing solely on local optimal choices, potentially leading to suboptimal solutions.

Question 16

Multiple choice

In the coin change problem implementation provided, which step occurs after sorting the coin denominations?

Select the smallest denomination.

Count coins based on frequency.

Subtract the coin denomination from the total amount.

Correct

Group coins into categories based on size.

Explanation

After sorting the coin denominations in descending order, the algorithm subtracts the denomination from the total amount until it can no longer do so.

Question 17

Multiple choice

Which algorithm can be characterized by both greedy choice property and optimal substructure?

Bubble Sort

Greedy algorithms

Correct

Dynamic Programming

Graph Traversal

Explanation

Greedy algorithms are characterized by both properties, which make them suitable for specific optimization problems.

Question 18

Multiple choice

What common misconception exists regarding the optimal solutions provided by greedy algorithms?

They guarantee optimal solutions for all problems.

Correct

They always require extensive computation.

Greedy algorithms are incapable of producing solutions.

They are always faster than other algorithms.

Explanation

A common misconception is that greedy algorithms provide optimal solutions for every problem, whereas they can only guarantee optimality for specific types.

Question 19

Multiple choice

How does the greedy algorithm determine which activities to select in the activity selection problem?

By evaluating both start and finish times.

By choosing based on random selection.

By primarily considering the finish times of activities.

Correct

By selecting activities with the longest duration.

Explanation

The greedy algorithm selects activities primarily based on their finish times to maximize the number of non-overlapping activities.

Question 20

Multiple choice

Which of the following properties is NOT a characteristic of greedy algorithms?

Greedy Choice Property

Optimal Substructure

Local Optimum Assumption

Correct

The solution is built incrementally

Explanation

The 'Local Optimum Assumption' is not a recognized property of greedy algorithms. Greedy algorithms rely on making local optimal choices and ensuring they can lead to a globally optimal solution, but they don't make assumptions about local optimums in the same way that the properties of greedy choice and optimal substructure do.