Software—Practice & Experience
An introduction to the analysis of algorithms
An introduction to the analysis of algorithms
PYTHIA: a knowledge-based system to select scientific algorithms
ACM Transactions on Mathematical Software (TOMS)
Neural network design
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
An empirical study of minimal storage sorting
Communications of the ACM
A high-speed sorting procedure
Communications of the ACM
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Asymptotic analysis of an optimized quicksort algorithm
Information Processing Letters
Algorithm Selection using Reinforcement Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Analysis of Shellsort and Related Algorithms
ESA '96 Proceedings of the Fourth Annual European Symposium on Algorithms
Algorithm selection for sorting and probabilistic inference: a machine learning-based approach
Algorithm selection for sorting and probabilistic inference: a machine learning-based approach
Building a new sort function for a C library
Software—Practice & Experience
Acceleration of sweep-line technique by employing smart quicksort
Information Sciences—Informatics and Computer Science: An International Journal
Bio-inspired and gradient-based algorithms to train MLPs: The influence of diversity
Information Sciences: an International Journal
A modeling approach to the evaluation of internal sorting methods
Information Sciences: an International Journal
Efficient unbalanced merge-sort
Information Sciences: an International Journal
Artificial neural network approach for solving fuzzy differential equations
Information Sciences: an International Journal
Reordering columns for smaller indexes
Information Sciences: an International Journal
IEEE Transactions on Computers
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Dempster Shafer neural network algorithm for land vehicle navigation application
Information Sciences: an International Journal
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Quicksort is one of the most popular sorting algorithms, it is based on a divide-and-conquer technique and has a wide acceptance as the fastest general-purpose sorting technique. Though it is successful in separating large partitions into small ones, quicksort runs slowly when it processes its small partitions, for which completing the sorting through using a different sorting algorithm is much plausible solution. This variant minimizes the overall execution time but it switches to a constant sorting algorithm at a constant cut-off point. To cope with this constancy problem, it has been suggested that a dynamic model which can choose the fastest sorting algorithm for the small partitions. The model includes continuation with quicksort so that the cut-off point is also more flexible. To implement this with an intelligent algorithm selection model, artificial neural networks are preferred due to their non-comparison, constant-time and low-cost architecture features. In spite of the fact that finding the best sorting algorithm by using a neural network causes some extra computational time, the gain in overall execution time is greater. As a result, a faster variant of quicksort has been implemented by using artificial neural network based algorithm selection approach. Experimental results of the proposed algorithm and the several other fast sorting algorithms have been presented, compared and discussed.