| Resumen |
Sorting data in a computer is maybe the most popular classical task in Computer Science. For the majority of applications the main goal is to minimize the number of comparisons and execution time that the sorting algorithm consumes. Sorting Networks are algorithms that perform exactly the same number of comparisons to order any input permutation for a given input data size. That is, each step does not depend on the result of a previous comparisons. Thus, designing Sorting Networks with a minimal number of comparisons becomes a very important task. However, it is an NP-hard problem. Actually, the optimal Sorting Networks with a minimal number comparisons (or at least close to the optimal) for small input data sizes from 3 to 16 are published in the specialized literature. Of course, these input data sizes are very small to be used in real world problems. In this work we propose a new strategy to improve the QuickSort performance by coupling it with some Sorting Networks to large input data. The results demonstrate it helps reducing the sorting execution time. |
