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Advancing Sorting Efficiency and Exploring Complex Applications in Algorithmic Design

Publish Year: 1403
Type: Conference paper
Language: English
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Document National Code:

CARSE08_036

Index date: 30 December 2024

Advancing Sorting Efficiency and Exploring Complex Applications in Algorithmic Design abstract

Sorting algorithms are central to computational theory and widely used in data-centricapplications across fields such as machine learning, data analysis, and computationalgeometry. This paper presents an in-depth analysis of sorting efficiency, focusing on classicalalgorithms (QuickSort, MergeSort, HeapSort) and their optimization through parallelization,hybrid memory, and advanced data structures. We review seminal works by Aho, Hopcroft,and Ullman (1983) and Knuth (1973), establishing a foundation for performance evaluationand optimization strategies. Recent advancements, including in-memory parallel sortingarchitectures like IMC-Sort (Li et al., 2020), are explored to enhance computational efficiency.Further, this study investigates complex applications of sorting algorithms, such as their usein unstructured video classification (Morris & Kender, 2009) and eco-efficiency modeling fortropical systems (Peters et al., 2013). A novel sorting approach based on identifying thelongest increasing subsequences is presented, building on our previous work (Akbarian &Keyhanipour, 2023) to achieve optimized sequence sorting. By integrating classicaltechniques with modern innovations, this paper contributes to the ongoing evolution ofsorting algorithms, highlighting their relevance in diverse domains and their potential to meetthe demands of future computational challenges.

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Advancing Sorting Efficiency and Exploring Complex Applications in Algorithmic Design authors

Alireza Akbarian

Computer Engineering Student of Sharif University of Technology, International Campus-Kish, Iran

Arian Akbarian

High School Mathematics Student, Kerman, Iran