Evolutionary Optimization in Engineering Design
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Keywords

Evolutionary optimization
Engineering design
Structural optimization
System design
Genetic algorithms
Genetic programming
Optimization algorithms

How to Cite

[1]
Ana Silva, “Evolutionary Optimization in Engineering Design”, Journal of Bioinformatics and Artificial Intelligence, vol. 2, no. 1, pp. 1–11, Apr. 2022, Accessed: Nov. 24, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/12

Abstract

Evolutionary optimization techniques have gained significant attention in engineering design for their ability to efficiently search complex design spaces and find optimal solutions. This paper provides a comprehensive analysis of the application of evolutionary optimization in engineering design tasks, including structural optimization, parameter tuning, and system design. We review the fundamental principles of evolutionary optimization algorithms, such as genetic algorithms, evolutionary strategies, and genetic programming, highlighting their strengths and limitations. Furthermore, we discuss various real-world engineering applications where evolutionary optimization has been successfully employed, showcasing its effectiveness in solving complex design problems. Through this analysis, we aim to provide insights into the best practices and future directions of evolutionary optimization in engineering design.

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References

Venigandla, Kamala. "Integrating RPA with AI and ML for Enhanced Diagnostic Accuracy in Healthcare." Power System Technology 46.4 (2022).

Pillai, Aravind Sasidharan. "A Natural Language Processing Approach to Grouping Students by Shared Interests." Journal of Empirical Social Science Studies 6.1 (2022): 1-16.

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