Recombinant Sort: N-Dimensional Cartesian Spaced Algorithm Designed from Synergetic Combination of Hashing, Bucket, Counting and Radix Sort

TL;DR

This paper introduces a novel N-dimensional Cartesian spaced sorting algorithm that combines multiple existing sorting techniques and employs hashing and dynamic programming to achieve linear time complexity, outperforming traditional methods.

Contribution

The paper presents a new multidimensional sorting algorithm that integrates hashing, bucket, counting, and radix sort techniques for improved efficiency and linear time complexity.

Findings

Achieves linear time complexity O(n) in all cases.

Outperforms existing sorting algorithms like merge and heap sort.

Demonstrates superior efficiency through comparative analysis.

Abstract

Sorting is an essential operation which is widely used and is fundamental to some very basic day to day utilities like searches, databases, social networks and much more. Optimizing this basic operation in terms of complexity as well as efficiency is cardinal. Optimization is achieved with respect to space and time complexities of the algorithm. In this paper, a novel left-field N-dimensional cartesian spaced sorting method is proposed by combining the best characteristics of bucket sort, counting sort and radix sort, in addition to employing hashing and dynamic programming for making the method more efficient. Comparison between the proposed sorting method and various existing sorting methods like bubble sort, insertion sort, selection sort, merge sort, heap sort, counting sort, bucket sort, etc., has also been performed. The time complexity of the proposed model is estimated to be linear i.e. O(n) for the best, average and worst cases, which is better than every sorting algorithm introduced till date.