Q1: 1. Which of the following is a characteristic of Greedy Algorithms?

• A) Backtracking
• B) Dynamic Programming
• C) Exhaustive Search
• D) Shortest Path

Q2: 2. In the context of Greedy Algorithms, what does the "greedy choice property" mean?

• A) Always selecting the largest item first
• B) Making the locally optimal choice at each stage
• C) Considering all possible solutions before making a decision
• D) Choosing the global optimal solution

Q3: 3. Which of the following is a classic example of a problem that can be solved using Greedy Algorithms?

• A) Sorting a list of integers
• B) Finding the shortest path in a graph
• C) Huffman coding
• D) Matrix multiplication

Q4: 4. In a Huffman coding algorithm, how are the frequencies of characters used to build the optimal prefix-free code?

• A) Characters are sorted alphabetically
• B) Characters with higher frequencies are assigned shorter codes
• C) Characters are grouped based on their frequency
• D) Characters with lower frequencies are assigned longer codes

Q5: 5. Which of the following is a disadvantage of Greedy Algorithms?

• A) They are difficult to implement
• B) They always guarantee the optimal solution
• C) They may not always produce the best solution
• D) They are computationally expensive

Q6: 6. The Knapsack problem can be solved using a Greedy Algorithm when

• A) Only one copy of each item is available
• B) Items have equal values and weights
• C) Items can be divided
• D) The knapsack has unlimited capacity

Q7: 7. Which of the following is a step in the process of designing a Greedy Algorithm?

• A) Backtracking
• B) Memoization
• C) Sorting
• D) Randomized algorithms

Q8: 8. Which of the following is an example of a problem that cannot be solved optimally using a Greedy Algorithm?

• A) Prim's algorithm for Minimum Spanning Tree
• B) Dijkstra's algorithm for Shortest Path
• C) Job Sequencing with Deadlines
• D) Fractional Knapsack Problem

Q9: 9. Which of the following is a property of Greedy Algorithms?

• A) They use dynamic programming
• B) They make decisions based on current information
• C) They always guarantee the optimal solution
• D) They are suitable for all types of problems

Q10: 10. The Interval Scheduling problem can be efficiently solved using a Greedy Algorithm when

• A) Jobs have equal lengths
• B) Jobs have equal start times
• C) Jobs are sorted by finish times
• D) Jobs are sorted by profit

Q11: 11. Which of the following is an example of a problem where Greedy Algorithms are commonly used?

• A) Traveling Salesman Problem
• B) Bin Packing Problem
• C) Longest Common Subsequence
• D) Floyd-Warshall algorithm

Q12: 12. Which of the following is a key concept in Greedy Algorithms?

• A) Memoization
• B) Greedy choice property
• C) Bellman-Ford algorithm
• D) Breadth-first Search

Q13: 13. In the context of Greedy Algorithms, what does the term "local optimization" refer to?

• A) Finding the optimal solution globally
• B) Making the best choice at each step
• C) Considering all possible solutions
• D) Iteratively improving the solution

Q14: 14. Which of the following problems can be solved using a Greedy Algorithm with a guarantee of optimality?

• A) Job Sequencing with Deadlines
• B) Minimum Spanning Tree
• C) Longest Increasing Subsequence
• D) Travelling Salesman Problem

Q15: 15. Which of the following algorithms is an example of a Greedy Algorithm for finding the shortest path in a graph?

• A) Bellman-Ford algorithm
• B) Dijkstra's algorithm
• C) Floyd-Warshall algorithm
• D) Prim's algorithm

Q16: 16. The Coin Change problem can be efficiently solved using a Greedy Algorithm when

• A) Coins have different denominations
• B) Coins have equal values
• C) Coins can be divided
• D) Coins have increasing denominations

Q17: 17. Which of the following problems is NOT typically suitable for solving using Greedy Algorithms?

• A) Fractional Knapsack Problem
• B) Prim's algorithm for Minimum Spanning Tree
• C) Job Sequencing with Deadlines
• D) Dijkstra's algorithm for Shortest Path

Q18: 18. What is the main advantage of Greedy Algorithms compared to other algorithmic techniques?

• A) They are always faster
• B) They are easier to implement
• C) They guarantee the optimal solution
• D) They are more versatile

Q19: 19. Which of the following problems can be efficiently solved using a Greedy Algorithm based on a specific property of the problem?

• A) Longest Common Subsequence
• B) Bipartite Matching
• C) Travelling Salesman Problem
• D) Coin Change problem with arbitrary denominations

Q20: 20. Which of the following statements is true regarding the behavior of Greedy Algorithms?

• A) They always backtrack to explore other options
• B) They make a series of locally optimal choices
• C) They require exhaustive search of all possibilities
• D) They prioritize the global optimal solution

Q21: 21. The Activity Selection problem can be efficiently solved using a Greedy Algorithm when

• A) Activities have equal durations
• B) Activities are sorted by start times
• C) Activities have equal profits
• D) Activities have increasing order of deadlines

Q22: 22. Which of the following problems can be optimally solved using a Greedy Algorithm based on a specific property of the problem?

• A) Longest Common Subsequence
• B) Minimum Spanning Tree
• C) Travelling Salesman Problem
• D) Shortest Path in a weighted graph

Q23: 23. In the context of Greedy Algorithms, what does the term "optimal substructure" mean?

• A) The solution can be constructed recursively from optimal solutions of subproblems
• B) The solution can be found by considering all possible choices
• C) The solution remains the same regardless of the input
• D) The solution is guaranteed to be the best possible

Q24: 24. Which of the following problems can be solved using a Greedy Algorithm by making decisions based on a specific property of the problem?

• A) Sorting a list of integers
• B) Huffman coding
• C) Matrix multiplication
• D) Finding the longest path in a graph

Q25: 25. Which of the following is a key aspect of Greedy Algorithms that differentiates them from other algorithmic techniques?

• A) They involve exhaustive search
• B) They guarantee the optimal solution
• C) They make decisions based on current information
• D) They require backtracking