The Computational Efficiency in Mathematical Algorithms

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:International Journal of Combinatorial Optimization Problems and Informatics vol. 16, no. 2 (2025), p. 191
मुख्य लेखक: Eric León Olivares
अन्य लेखक: Márquez Strociak, Luis Carlos, Mayra Lorena González Mosqueda, Karla Martínez Tapia, Salvador Martínez Pagola, Eric Simancas Acevedo
प्रकाशित:
International Journal of Combinatorial Optimization Problems & Informatics
विषय:
ऑनलाइन पहुंच:Citation/Abstract
Full Text - PDF
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022 |a 2007-1558 
024 7 |a 10.61467/2007.1558.2025.v16i2.1081  |2 doi 
035 |a 3182339083 
045 2 |b d20250401  |b d20250630 
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100 1 |a Eric León Olivares 
245 1 |a The Computational Efficiency in Mathematical Algorithms 
260 |b International Journal of Combinatorial Optimization Problems & Informatics  |c 2025 
513 |a Journal Article 
520 3 |a The implementation of mathematical algorithms plays a fundamental role in computational efficiency. Sequential programming, which processes instructions in a linear manner, often struggles with large data volumes due to its inherent limitations. In contrast, parallel programming distributes tasks across multiple cores, significantly reducing processing times and improving overall performance. This paper presents a comparative analysis of both approaches and their relevance in Systems Engineering, where computational optimization is critical. To this end, we implement and evaluate the Sobel algorithm—commonly used for edge detection in images—in both sequential and parallel modes. The implementation is carried out in Python, leveraging the NumPy, OpenCV, and Multiprocessing libraries. This study analyzes the conditions under which parallelization enhances performance and identifies scenarios where process overhead may negate its benefits, thus establishing fundamental criteria for applying these techniques to solve mathematical problems in engineering. The source code is available on GitHub at: [GitHub Repository]. 
653 |a Systems engineering 
653 |a Algorithms 
653 |a Source code 
653 |a Parallel programming 
653 |a Multiprocessing 
653 |a Edge detection 
653 |a Computational efficiency 
653 |a Big Data 
653 |a Optimization 
653 |a Supercomputers 
653 |a Measurement techniques 
653 |a Linear programming 
653 |a Engineering 
653 |a Libraries 
653 |a Informatics 
653 |a Mathematical problems 
653 |a Workloads 
653 |a High performance computing 
653 |a Efficiency 
653 |a Comparative analysis 
700 1 |a Márquez Strociak, Luis Carlos 
700 1 |a Mayra Lorena González Mosqueda 
700 1 |a Karla Martínez Tapia 
700 1 |a Salvador Martínez Pagola 
700 1 |a Eric Simancas Acevedo 
773 0 |t International Journal of Combinatorial Optimization Problems and Informatics  |g vol. 16, no. 2 (2025), p. 191 
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856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3182339083/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3182339083/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch