Thirty Years of Progress in Single/Multi-disciplinary Design Optimization with Evolutionary Algorithms and Game Strategies in Aeronautics and Civil Engineering

Périaux, Jacques; Tuovinen, Tero

doi:10.1007/978-3-031-29082-4_24

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Other1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Optimal Leg Linkage Design for Horizontal Propel of a Walking Robot Using Non-Dominated Sorting Genetic Algorithm

Omarov,

Ibrayev,

Ibrayeva

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

Optimal Leg Linkage Design for Horizontal Propel of a Walking Robot Using Non-Dominated Sorting Genetic Algorithm

Omarov,

Ibrayev,

Ibrayeva

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

Multi-Objective Optimization in Asynchronous Environments: An Evolutionary Game Theory Approach

Jarosz,

Marszałek

2024

2024 32nd International Conference on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)

View full text Add to dashboard Cite

Framework for metamodel-based design optimization considering product performance and assembly process complexity

Eremeev,

Cock,

Devriendt

et al. 2024

SIMULATION

View full text Add to dashboard Cite

This paper proposes a method for simultaneous evaluation of the assembly process complexity together with the performance of the future product. It allows for product design optimization, considering different aspects of the future design at the early stage of the development process. The proposed method, embodied in a fully automated framework, substitutes the traditional sequential development process with a more efficient and rapid combined procedure, which addresses multiple design aspects simultaneously. Design for assembly (DFA) rules, used as quantitative metrics of the ease-of-assembly of the whole product and individual assembly operations, are automatically evaluated together with performance metrics, estimated based on finite element (FE) simulations. The direct solution to this optimization problem might be inefficient or impossible since it requires the recurrent evaluation of computationally expensive discrete and continuous functions with unknown behavior that represent the optimization objectives and constraints. For that reason, the proposed framework employs regression models based on the Gaussian process and artificial neural networks, thus achieving the optimal design of a product as a result of metamodel-based design optimization (MBDO). The suggested approach is demonstrated in the optimization of a gearbox assembly, considering its mechanical performance and assembly process. Comparing the results of the metamodel-based and direct design optimization shows that MBDO allows finding a better solution using a three times smaller computational budget. In addition, analysis of the results obtained using stationary sampling data sets of different sizes highlighted the limitations of the employed sampling procedure.

show abstract

Thirty Years of Progress in Single/Multi-disciplinary Design Optimization with Evolutionary Algorithms and Game Strategies in Aeronautics and Civil Engineering

Cited by 3 publications

References 39 publications

Optimal Leg Linkage Design for Horizontal Propel of a Walking Robot Using Non-Dominated Sorting Genetic Algorithm

Optimal Leg Linkage Design for Horizontal Propel of a Walking Robot Using Non-Dominated Sorting Genetic Algorithm

Multi-Objective Optimization in Asynchronous Environments: An Evolutionary Game Theory Approach

Framework for metamodel-based design optimization considering product performance and assembly process complexity

Contact Info

Product

Resources

About