journal article·2020-02

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

ZhenZhou Wang, Adam Sobey

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Abstract

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.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Multi-Objective Optimization Algorithms · Topology Optimization in Engineering · Composite Structure Analysis and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (100+)

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