There are various sorting algorithms, each with its unique advantages and disadvantages. Some of the other well-known sorting algorithms include Bubble Sort, Insertion Sort, Selection Sort, Merge Sort, Quick Sort, and Radix Sort.

Bubble Sort is a simple sorting algorithm that repeatedly swaps adjacent elements if they are in the wrong order. However, it has a time complexity of O(n^2) and is not efficient for large datasets.

Insertion Sort is another simple sorting algorithm that works by inserting each element in its correct position, one at a time. Its time complexity is also O(n^2), but it performs better than Bubble Sort in practice.

Selection Sort is an in-place comparison-based sorting algorithm that works by repeatedly finding the minimum element and swapping it with the element at the beginning of the unsorted part of the array. It has a time complexity of O(n^2) and is also not very efficient.

Merge Sort is a divide-and-conquer algorithm that works by dividing the input array into two halves, sorting each half separately, and then merging them back together. It has a time complexity of O(n log n) and is stable, but it requires additional memory.

Quick Sort is another divide-and-conquer algorithm that works by partitioning the input array around a pivot element and then recursively sorting the subarrays. It has a time complexity of O(n log n) on average and is efficient in practice, but its worst-case time complexity can be O(n^2) if the pivot is not selected carefully.

Radix Sort is a non-comparison-based sorting algorithm that works by sorting elements based on their digits or other significant digits. It has a time complexity of O(kn), where k is the number of digits in the input elements, and it can be more efficient than comparison-based algorithms for certain types of input data.

Each of these sorting algorithms has its advantages and disadvantages, and the choice of which one to use depends on various factors such as the size of the dataset, the nature of the input data, and the desired time and space complexity. Some algorithms, like Quick Sort and Merge Sort, can be more efficient than Heap Sort for large datasets, while others like Bubble Sort and Selection Sort are less efficient than Heap Sort in practice.
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