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Which of the following is NOT a valid implementation of Dijkstra's algorithm?

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Question: Which of the following is NOT a valid implementation of Dijkstra\'s algorithm?

Options:

  1. Using an adjacency matrix.
  2. Using an adjacency list with a binary heap.
  3. Using a linked list for the priority queue.
  4. Using a Fibonacci heap.

Correct Answer: Using a linked list for the priority queue.

Solution: 

Using a linked list for the priority queue is not efficient for Dijkstra\'s algorithm, as it does not provide optimal time complexity for extracting the minimum.

Which of the following is NOT a valid implementation of Dijkstra's algorithm?

Practice Questions

Q1
Which of the following is NOT a valid implementation of Dijkstra's algorithm?
  1. Using an adjacency matrix.
  2. Using an adjacency list with a binary heap.
  3. Using a linked list for the priority queue.
  4. Using a Fibonacci heap.

Questions & Step-by-Step Solutions

Which of the following is NOT a valid implementation of Dijkstra's algorithm?
  • Step 1: Understand what Dijkstra's algorithm is. It is a method used to find the shortest path from a starting point to all other points in a graph.
  • Step 2: Learn about priority queues. A priority queue is a data structure that allows you to efficiently get the item with the highest priority (in this case, the smallest distance).
  • Step 3: Identify common data structures used for priority queues, such as binary heaps or Fibonacci heaps, which allow for efficient extraction of the minimum element.
  • Step 4: Consider using a linked list as a priority queue. In a linked list, to find the minimum element, you have to check each element one by one, which is slow.
  • Step 5: Compare the efficiency of using a linked list versus a binary heap. A binary heap allows you to find and remove the minimum element much faster than a linked list.
  • Step 6: Conclude that using a linked list for the priority queue in Dijkstra's algorithm is NOT a valid implementation because it does not provide optimal time complexity.
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