Exploring Perfect Sorting Algorithms

In summary, quick sort is not the most efficient algorithm as its worst case complexity is O(n^2). However, it is quick and easy to code and performs well in most cases due to its inner loop fitting in the CPU cache. Merge and heap sorts have a worst case complexity of O(n ln n) and are slower in practice. Merge sort can outperform quicksort in certain cases, such as when using pointers to data with a larger average compare size. For truly random data, a hybrid radix/merge sort has been found to be the fastest, but requires more memory. Previous discussions on sorting have also included test results, with the first link providing some results in post #16.
  • #1
viv0411
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0
Is quick sort the most efficient algorithm or there is a possibility of a perfect sorting algorithm to be discovered?
 
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  • #2
quick sort isn't even the most efficient current algorithm, it's worst case is O(n^2) but is quick and easy to code and the inner loop fits in the CPU cache so is fast enough normally.

merge and heap sorts are both O(n ln n) worst case but in practice are slower.
 
  • #3
Merge sort can be faster than quicksort, especially when using pointers to data where the average compare size (before a mismatch) is greater than a pointer size. For true random data, I used a hybrid radix (bucket) / merge sort, which was the fastest, but required a large amount of memory.

Previous threads on sorting. I included some test results in post #16 of the thread in the first link:

https://www.physicsforums.com/showthread.php?t=218369

https://www.physicsforums.com/showthread.php?t=181589
 

Related to Exploring Perfect Sorting Algorithms

1. What is a perfect sorting algorithm?

A perfect sorting algorithm is an algorithm that is able to sort any given set of data in the most optimal way possible, with the least amount of comparisons and swaps.

2. What makes a sorting algorithm perfect?

A perfect sorting algorithm must have a worst-case time complexity of O(nlogn), where n is the number of elements in the input data. It should also be able to handle duplicate elements and have an efficient implementation.

3. What are some examples of perfect sorting algorithms?

Some examples of perfect sorting algorithms include merge sort, quick sort, and heap sort. These algorithms have a worst-case time complexity of O(nlogn) and are able to sort any given data set efficiently.

4. How do perfect sorting algorithms differ from other sorting algorithms?

Unlike other sorting algorithms, perfect sorting algorithms have a guaranteed worst-case time complexity of O(nlogn). This means that no matter the input data, the algorithm will always perform optimally, making it the most efficient way to sort data.

5. Can perfect sorting algorithms be used for any type of data?

Yes, perfect sorting algorithms can be used for any type of data as long as the data can be compared and swapped. This means they can be used for numbers, strings, objects, and other data types.

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