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.
翻译:排序是一项基本操作, 广泛使用, 并且对于日常公用设施( 如搜索、 数据库、 社交网络等等) 一些最基本的日常公用设施来说至关重要。 从复杂性和效率的角度优化这一基本操作是最重要的。 在算法的空间和时间复杂性方面实现了最佳化。 在本文中, 提出了一个新颖的左侧野野外N- 维度的卡通斯空间排序方法, 其方法是结合水桶分类、 计数分类和 radex 类的最佳特性, 以及使用散列和动态编程来提高方法的效率。 比较了拟议的排序方法和各种现有排序方法, 如泡泡类、 插入类、 选择类、 合并类、 堆积类、 计数类、 桶类等。 所拟议的模型的时间复杂性估计为线性, 也就是说, 最佳、 平均 和 最坏的情况为 O (n), 这比迄今为止引入的每次排序算法都要好 。