Merge Sorted Stacks in Ascending Order Using 4n-4 Moves

  • Thread starter transgalactic
  • Start date
In summary: In this problem, the invariant is the order of the elements in the stacks. If you change the order of the elements in the stacks, then the order of the elements in the final stack will be different, but the invariant is still preserved. In summary, the problem asks for a method that puts all of the objects from stacks S1 and S2 into stack S3 in accended order, plus we have to accomplish this using 4n-4 moves. However, this problem is not feasible to solve using the given parameters.
  • #1
transgalactic
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i have two stack S1 and S2 the total amount of objects
in them is "n"
in both stack all the objects are sorted in accending order

(the biggest number is on top the smallest number is on the bottom)

and that's the way it goes in both stacks

the question asks me to build a method which
puts all of the objects from stacks S1 and S2 into stack S3
in accended order plus we have to accomplish this using 4n-4 moves ??
(the biggest number is on top the smallest number is on the bottom)

i tried to solve that by
flipping the stacks using the S3 so they will be sorted from the smallest
to the biggest
taking two templorary variables pop each object from each stack
into the temporary variable
and then we compare them and the smallest goes to S3
and the other one waits till we have an object from the other stack which is smaller than him,
and then we have to flip S3 in order have the biggest on top
also i tried using TOP commang but i found out that
its implementation also has push and pop in it.
but in that way we have more than 4n-4 moves
 
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  • #2
This is the http://en.wikipedia.org/wiki/Tower_of_Hanoi" Problem if I am not mistaken. This should get you started.
 
Last edited by a moderator:
  • #3
a. Move S1 to S3 = S1'
b. Move S2 to S1 = S2'.
c. Move S3 to S2 = S1.
*the two stacks are exchanged and (their) one order reversed in 3n/2 moves.
d. now you can continue.

hint: repeat a.b,c to have 6n/2 moves.
 
Last edited:
  • #4
transgalactic said:
i tried to solve that by
flipping the stacks using the S3 so they will be sorted from the smallest
to the biggest
This along requires 2n operations. Not a good start. Not only that, you will have to reverse the temporary stack at the end, costing another 2n operations. You have already exceeded the budget with this approach and you haven't even started building the temporary stack. Solution: build the temporary stack in reverse order.
and then we compare them and the smallest goes to S3
You don't have to do this to the bitter end. You can save some operations by avoiding putting all of the elements on the temporary stack. At some point you will have emptied both stacks, leaving you with two elements in the temporary variables and n-2 elements in the temporary stack. Why not put the two temporary variables directly where they belong instead?

It helps to think of invariants, if you have been taught that concept.
 

1. How does the algorithm for merging sorted stacks work?

The algorithm for merging sorted stacks follows a simple process of comparing the top elements of the two stacks and placing the smaller element on top of the merged stack. This process is repeated until one of the stacks is empty, and then the remaining elements from the other stack are placed on top of the merged stack. This ensures that the merged stack is also sorted in ascending order.

2. How many moves are needed to merge two sorted stacks of 4n elements?

To merge two sorted stacks of 4n elements, 4n-4 moves are needed. This is because each iteration of the merging process involves 4 moves (2 comparisons and 2 push operations), and there are n-1 iterations needed to merge n elements. Therefore, for 4n elements, the total number of moves required is (n-1) x 4 = 4n-4 moves.

3. Can the algorithm for merging sorted stacks be used for stacks with non-numeric elements?

Yes, the algorithm for merging sorted stacks can be used for stacks with non-numeric elements as long as the elements can be compared and sorted. This means that the elements must have some sort of ordering, such as alphabetical or numerical, to be able to determine which element is smaller or larger.

4. Is the algorithm for merging sorted stacks in ascending order efficient?

Yes, the algorithm for merging sorted stacks in ascending order is considered efficient as it has a time complexity of O(n), where n is the total number of elements in the stacks. This means that the time it takes to merge the stacks increases linearly with the number of elements, making it a fast and efficient solution.

5. Can the algorithm for merging sorted stacks be used for more than two stacks?

Yes, the algorithm for merging sorted stacks can be extended to merge more than two stacks. The process would involve merging two stacks at a time and then repeating this process until all the stacks are merged. This would still follow the same principle of comparing top elements and placing them in ascending order on the merged stack.

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