Top MCQs on Greedy Algorithms with Answers

Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. So the problems where choosing locally optimal also leads to global solution are the best fit for Greedy. More on Greedy Algorithm

Greedy Algorithms Quiz

Greedy Algorithms Quiz

Question 1

A networking company uses a compression technique to encode the message before transmitting over the network. Suppose the message contains the following characters with their frequency: 

C

character   Frequency
    a	          5
    b             9
    c             12
    d             13
    e             16
    f             45

Note : Each character in input message takes 1 byte. If the compression technique used is Huffman Coding, how many bits will be saved in the message?

Cross

224

Cross

800

Tick

576

Cross

324



Question 1-Explanation: 
Total number of characters in the message = 100. 
Each character takes 1 byte. So total number of bits needed = 800.

After Huffman Coding, the characters can be represented with:
f: 0
c: 100
d: 101
a: 1100
b: 1101
e: 111
Total number of bits needed = 224
Hence, number of bits saved = 800 - 224 = 576
See here for complete explanation and algorithm.
Question 2

What is the time complexity of Huffman Coding?

Cross

O(N)

Tick

O(NlogN)

Cross

O(N(logN)^2)

Cross

O(N^2)



Question 2-Explanation: 

O(nlogn) where n is the number of unique characters. If there are n nodes, extractMin() is called 2*(n – 1) times. extractMin() takes O(logn) time as it calls minHeapify(). So, overall complexity is O(nlogn). 

Question 3

In question #2, which of the following represents the word "dead"?

Cross

1011111100101

Cross

0100000011010

Tick

Both A and B

Cross

None of these



Question 3-Explanation: 
character   code-word
    f          0
    c          100
    d          101
    a          1100
    b          1101
    e          111

The word dead can be represented as: 101 111 1100 101 However, the alternative codeword can also be found by assigning 1 to the left edge and 0 to the right edge of the tree, i.e. dead can also be represented as: 010 000 0011 010 See here for more details of the algorithm.

Question 4

Which of the following is true about Kruskal and Prim MST algorithms? 

Assume that Prim is implemented for adjacency list representation using Binary Heap and Kruskal is implemented using union by rank.

Tick

Worst case time complexity of both algorithms is same.

Cross

Worst case time complexity of Kruskal is better than Prim

Cross

Worst case time complexity of Prim is better than Kruskal

Cross

None of these



Question 4-Explanation: 

Kruskal's algorithm and Prim's algorithm are both used to find the minimum spanning tree (MST) of a weighted graph, but they have different approaches.

Kruskal's algorithm: Kruskal's algorithm sorts the edges of the graph in the non-decreasing order of their weights and then iterates over the sorted edges, adding them to the MST if they do not create a cycle. It uses the disjoint-set data structure with the union by rank and path compression to efficiently detect cycles and maintain the disjoint sets.

The time complexity of Kruskal's algorithm is primarily determined by the sorting step, which takes O(E log E) time, where E is the number of edges in the graph. The union-find operations for cycle detection take nearly constant time per operation, approximately O(α(V)), where α is the inverse Ackermann function and V is the number of vertices.

Prim's algorithm: Prim's algorithm starts with an arbitrary vertex and grows the MST by adding the minimum-weight edge that connects a vertex in the MST to a vertex outside the MST. It commonly uses a priority queue, often implemented with a binary heap, to efficiently select the minimum-weight edge at each step.

For Prim's algorithm with a binary heap implementation, the time complexity is O((E + V) log V), where E is the number of edges and V is the number of vertices in the graph. This time complexity arises from performing V extract-min operations on the binary heap and updating the key values of adjacent vertices.

Comparing the time complexities of both algorithms:

  • Kruskal's algorithm: O(E log E + α(V))
  • Prim's algorithm (with binary heap): O((E + V) log V)

Overall, the Worst case time complexity of both algorithms is the same.

For more reference Please visit:

Hence Option (A) is correct.

Question 5

Which of the following is true about Huffman Coding?

Cross

Huffman coding may become lossy in some cases

Cross

Huffman Codes may not be optimal lossless codes in some cases

Tick

In Huffman coding, no code is prefix of any other code.

Cross

All of the above



Question 5-Explanation: 

Huffman coding is a lossless data compression algorithm. The codes assigned to input characters are Prefix Codes, means the codes are assigned in such a way that the code assigned to one character is not prefix of code assigned to any other character. This is how Huffman Coding makes sure that there is no ambiguity when decoding.

Question 6
Suppose the letters a, b, c, d, e, f have probabilities 1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. Which of the following is the Huffman code for the letter a, b, c, d, e, f?
Tick
0, 10, 110, 1110, 11110, 11111
Cross
11, 10, 011, 010, 001, 000
Cross
11, 10, 01, 001, 0001, 0000
Cross
110, 100, 010, 000, 001, 111


Question 6-Explanation: 
We get the following Huffman Tree after applying Huffman Coding Algorithm. The idea is to keep the least probable characters as low as possible by picking them first.
The letters a, b, c, d, e, f have probabilities 
1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. 

                 1
               /   \\
              /     \\
             1/2    a(1/2)
            /  \\
           /    \\
          1/4  b(1/4) 
         /   \\
        /     \\
       1/8   c(1/8) 
      /  \\
     /    \\
   1/16  d(1/16)
  /  \\
 e    f
Question 7
Suppose the letters a, b, c, d, e, f have probabilities 1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. What is the average length of Huffman codes?
Cross
3
Cross
2.1875
Cross
2.25
Tick
1.9375


Question 7-Explanation: 
We get the following Huffman Tree after applying Huffman Coding Algorithm. The idea is to keep the least probable characters as low as possible by picking them first.
The letters a, b, c, d, e, f have probabilities 
1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. 

                 1
               /   \\
              /     \\
             1/2    a(1/2)
            /  \\
           /    \\
          1/4  b(1/4) 
         /   \\
        /     \\
       1/8   c(1/8) 
      /  \\
     /    \\
   1/16  d(1/16)
  /  \\
 e    f
The average length = (1*1/2 + 2*1/4 + 3*1/8 + 4*1/16 + 5*1/32 + 5*1/32)
                   = 1.9375 
Question 8

Consider the undirected graph below:  Using Prim's algorithm to construct a minimum spanning tree starting with node A, which one of the following sequences of edges represents a possible order in which the edges would be added to construct the minimum spanning tree?

 

Cross

(E, G), (C, F), (F, G), (A, D), (A, B), (A, C)

Cross

(A, D), (A, B), (A, C), (C, F), (G, E), (F, G)

Cross

(A, B), (A, D), (D, F), (F, G), (G, E), (F, C)

Tick

(A, D), (A, B), (D, F), (F, C), (F, G), (G, E)



Question 8-Explanation: 

A. False 
The idea behind Prim’s algorithm is to construct a spanning tree – means all vertices must be connected but here vertices are disconnected

B. False 
The idea behind Prim’s algorithm is to construct a spanning tree – means all vertices must be connected but here vertices are disconnected

C. False. 
Prim’s is a greedy algorithm and At every step, it considers all the edges that connect the two sets, and picks the minimum weight edge from these edges. In this option, since weight of AD<AB, so AD must be picked up first (which is not true as per the options).

D.TRUE.

Therefore, Answer is D

Prim’s algorithm is also a Greedy algorithm. It starts with an empty spanning tree. The idea is to maintain two sets of vertices. The first set contains the vertices already included in the MST, the other set contains the vertices not yet included. At every step, it considers all the edges that connect the two sets, and picks the minimum weight edge from these edges. After picking the edge, it moves the other endpoint of the edge to the set containing MST.

Read more at: Prim’s Minimum Spanning Tree (MST)

Question 9

Consider the weights and values of items listed below. Note that there is only one unit of each item.

Question


The task is to pick a subset of these items such that their total weight is no more than 11 Kgs and their total value is maximized. Moreover, no item may be split. The total value of items picked by an optimal algorithm is denoted by Vopt. A greedy algorithm sorts the items by their value-to-weight ratios in descending order and packs them greedily, starting from the first item in the ordered list. The total value of items picked by the greedy algorithm is denoted by Vgreedy. The value of Vopt − Vgreedy is ______ . 

Tick

16

Cross

8

Cross

44

Cross

60



Question 9-Explanation: 

First we will pick item_4 (Value weight ratio is highest). Second highest is item_1, but cannot be picked because of its weight. Now item_3 shall be picked. item_2 cannot be included because of its weight. Therefore, overall profit by Vgreedy = 20+24 = 44 Hence, Vopt - Vgreedy = 60-44 = 16 So, answer is 16.

Question 10

A text is made up of the characters a, b, c, d, e each occurring with the probability 0.11, 0.40, 0.16, 0.09 and 0.24 respectively. The optimal Huffman coding technique will have the average length of:

Cross

2.40

Tick

2.16

Cross

2.26

Cross

2.15



Question 10-Explanation: 

a = 0.11 b = 0.40 c = 0.16 d = 0.09 e = 0.24 we will draw a huffman tree: \"huffman1\" now huffman coding for character:

 a = 1111
      b = 0
      c = 110
      d = 1111
      e = 10
length for each character = no of bits * frequency of occurrence:
a = 4 * 0.11
  = 0.44
b = 1 * 0.4
  =  0.4
c = 3 * 0.16
  = 0.48
d = 4 * 0.09
  =  0.36 
e = 2 * 0.24
  = 0.48
Now add these lenght for average length:
 0.44 + 0.4 + 0.48 + 0.36 + 0.48 = 2.16

So, option (B) is correct.

There are 20 questions to complete.


  • Last Updated : 27 Sep, 2023

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