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This is a Quantitative Study study.

October 20, 2025Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

A hybrid genetic and evolutionary algorithm approach for multi-objective optimization in structural mechanics

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Authors

TTTrần Thị Minh TâmTon Duc Thang University TNThanh Q. NguyenHo Chi Minh City University of Transport PNPhuoc T. NguyenHo Chi Minh City Open University

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Implication

This framework integrates genetic algorithms and multi-objective methods for optimizing structural mechanics, highlighting improved accuracy and reliability.

Key Points

The proposed methods enhance multi-objective optimization in structural mechanics, showing significant precision.
Validation through mechanical case studies like truss structures and fluid-structure interactions confirms the methods' effectiveness.
Integrating isogeometric analysis helps improve boundary representation accuracy in structural problems.
These methods provide a reliable strategy for optimizing complex engineering applications across different structures.

Cite This Study

Tâm et al. (2025) studied this question.

synapsesocial.com/papers/68f58f68ece7a5b64f471437 https://doi.org/10.1177/09544062251377849

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Implication

This framework integrates genetic algorithms and multi-objective methods for optimizing structural mechanics, highlighting improved accuracy and reliability.

A hybrid genetic and evolutionary algorithm approach for multi-objective optimization in structural mechanics

Discussion

Member takes

Implication

Key Points

Cite This Study

A hybrid genetic and evolutionary algorithm approach for multi-objective optimization in structural mechanics

Discussion

Member takes

Implication

Key Points

Cite This Study

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