Linearithmic Mean and Standard Deviation Sorting Method (LMDSM): Efficient and Stable Algorithm

Sorting algorithms have significance in the field of big data and high-performance computing, where effective data processing is of major significance. This paper presents the Linearithmic Mean and Standard Deviation Sorting Method (LMDSM), a new sorting method designed to handle enormous datasets and complex computational environments. Further this paper present a comprehensive comparative analysis of LMDSM with conventional sorting algorithms like Merge Sort and Quick Sort, emphasizing its efficiency and stability in different scenarios. LMDSM consistently outperforms other sorting algorithms in terms of sorting time when tested on arrays of 850,292 data in various orders. Furthermore, paper provide a rigorous theoretical analysis of LMDSM, encompassing its recurrence relation and time complexity derivation. Our research highlights the importance of LMDSM as an effective option for organizing jobs in current computing environments, providing significant importance in speed and reliability.

Authors

Publication Details

Journal
Panamerican mathematical journal.
Published
2024-10-01
DOI
https://doi.org/10.52783/pmj.v34.i3.1796
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Linearithmic Mean and Standard Deviation Sorting Method (LMDSM): Efficient and Stable Algorithm

Haribhau R. Bhapkar
Panamerican mathematical journal.
Advanced Algorithms and Applications
article

Linearithmic Mean and Standard Deviation Sorting Method (LMDSM): Efficient and Stable Algorithm

Haribhau R. Bhapkar
article en

Abstract

Sorting algorithms have significance in the field of big data and high-performance computing, where effective data processing is of major significance. This paper presents the Linearithmic Mean and Standard Deviation Sorting Method (LMDSM), a new sorting method designed to handle enormous datasets and complex computational environments. Further this paper present a comprehensive comparative analysis of LMDSM with conventional sorting algorithms like Merge Sort and Quick Sort, emphasizing its efficiency and stability in different scenarios. LMDSM consistently outperforms other sorting algorithms in terms of sorting time when tested on arrays of 850,292 data in various orders. Furthermore, paper provide a rigorous theoretical analysis of LMDSM, encompassing its recurrence relation and time complexity derivation. Our research highlights the importance of LMDSM as an effective option for organizing jobs in current computing environments, providing significant importance in speed and reliability.

Panamerican mathematical journal.Vol. 34(3)
Industry, innovation and infrastructure
Openalex Percentile: Top 76%
Advanced Algorithms and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Linearithmic Mean and Standard Deviation Sorting Method (LMDSM): Efficient and Stable Algorithm — Haribhau R. Bhapkar · Panamerican mathematical journal. (2024) | TGRS Research Map | TGRS