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Genetic algorithms in materials design and processing
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DOI：10.1179/095066004225021909.png)
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Genetic algorithms (GAs) are biologically inspired computing techniques, which tend to mimic the basic Darwinian concepts of natural selection. They are highly robust and efficient for most engineering optimising studies. Although a late entrant in the materials arena, GAs based studies are increasingly making their presence felt in many different aspects of this discipline. In recent times, GAs have been successfully used in numerous problems in the areas of atomistic material design, alloy design, polymer processing, powder compaction and sintering, ferrous production metallurgy, continuous casting, metal rolling, metal cutting, welding, and so on. The present review attempts to present the state of the art in this area. It includes three broad sections given as: fundamentals of genetic algorithms, genetic algorithms in materials design, and genetic algorithms in materials processing. The first section provides the reader with the basic concepts and the intricacies associated with this novel technique. The following section presents a detailed account of the usage of GAs to design various materials, predominantly at the atomic level. The third section aims to capture the process of applicability of GAs in numerous materials processing operations. A thorough literature search and critical analysis of the research conducted so far is provided, and attempts have been made to demonstrate how one single methodology can be utilised to study virtually every area of the vast materials discipline.
Keyword:
genetic algorithms
evolutionary computations
modelling
simulation
optimisation
materials design
materials processing
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