Articles
Genetic Algorithm Optimization - Principles and Applications: Analyzing the principles and applications of genetic algorithms (GAs) for optimization tasks in various domains, including engineering, finance, and scheduling
Published 17-04-2023
Keywords
- Genetic algorithms,
- Optimization,
- Engineering,
- Finance,
- Scheduling
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
[1]
Prof. Jose Rodriguez, “Genetic Algorithm Optimization - Principles and Applications: Analyzing the principles and applications of genetic algorithms (GAs) for optimization tasks in various domains, including engineering, finance, and scheduling”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, pp. 28–38, Apr. 2023, Accessed: Nov. 22, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/3
Abstract
Genetic algorithms (GAs) are a class of optimization algorithms inspired by the principles of natural selection and genetics. They have been widely applied to solve complex optimization problems in various domains due to their effectiveness and flexibility. This paper provides a comprehensive analysis of the principles and applications of genetic algorithms, focusing on their use in engineering, finance, and scheduling.
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