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A comparative review between genetic algorithm use in composite optimisation and the state-of-the-art in evolutionary computation

A comparative review between genetic algorithm use in composite optimisation and the state-of-the-art in evolutionary computation
A comparative review between genetic algorithm use in composite optimisation and the state-of-the-art in evolutionary computation
The task of providing optimal composite structures is increasingly difficult. New analysis approaches seek to model the material at the fibre/matrix scale and increasingly more control is sought over the material, for example optimising individual tows, and the structure, where new manufacturing techniques are proposed that will allow revolutionary new topologies. This additional complexity will stretch design engineers and as such it is important that state-of-the-art design methods are implemented to help take advantage of these exciting new opportunities, including computational optimisation methods. To determine best practice and the current limitations of the techniques a review of Genetic Algorithms in optimisation of composite materials and structures is performed over the last 10 years. This is compared to a technical review of the developments of Genetic Algorithms in the evolutionary computation literature. By better understanding how Genetic Algorithms are used in composite structures and comparing to evolutionary computational literature, recommendations are provided to help increase the use of Genetic Algorithms in solving composite optimisation problems in the future.
genetic algorithm (GA), Evolutionary computation, composite structures, Literature review, multi-objective optimisation, Many-objective optimisation
0263-8223
Wang, Zhenzhou
29dd1956-ff16-4c8e-ba23-b8c955a269e1
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Wang, Zhenzhou
29dd1956-ff16-4c8e-ba23-b8c955a269e1
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28

Wang, Zhenzhou and Sobey, Adam (2020) A comparative review between genetic algorithm use in composite optimisation and the state-of-the-art in evolutionary computation. Composite Structures, 233, [111739]. (doi:10.1016/j.compstruct.2019.111739).

Record type: Article

Abstract

The task of providing optimal composite structures is increasingly difficult. New analysis approaches seek to model the material at the fibre/matrix scale and increasingly more control is sought over the material, for example optimising individual tows, and the structure, where new manufacturing techniques are proposed that will allow revolutionary new topologies. This additional complexity will stretch design engineers and as such it is important that state-of-the-art design methods are implemented to help take advantage of these exciting new opportunities, including computational optimisation methods. To determine best practice and the current limitations of the techniques a review of Genetic Algorithms in optimisation of composite materials and structures is performed over the last 10 years. This is compared to a technical review of the developments of Genetic Algorithms in the evolutionary computation literature. By better understanding how Genetic Algorithms are used in composite structures and comparing to evolutionary computational literature, recommendations are provided to help increase the use of Genetic Algorithms in solving composite optimisation problems in the future.

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Final Version of the Paper Manuscript - Accepted Manuscript
Restricted to Repository staff only until 26 November 2020.
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More information

Accepted/In Press date: 26 November 2019
e-pub ahead of print date: 30 November 2019
Published date: February 2020
Keywords: genetic algorithm (GA), Evolutionary computation, composite structures, Literature review, multi-objective optimisation, Many-objective optimisation

Identifiers

Local EPrints ID: 436192
URI: http://eprints.soton.ac.uk/id/eprint/436192
ISSN: 0263-8223
PURE UUID: 0c4ab97c-5819-46f4-b016-a46710a33e84
ORCID for Zhenzhou Wang: ORCID iD orcid.org/0000-0003-3926-070X
ORCID for Adam Sobey: ORCID iD orcid.org/0000-0001-6880-8338

Catalogue record

Date deposited: 03 Dec 2019 17:30
Last modified: 27 Jan 2020 13:50

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