Genetic Algorithms, a Nature-Inspired Tool: Survey of Applications in Materials Science and Related Fields

Abstract

Genetic algorithms (GAs) are a tool used to solve high-complexity computational problems. Apart from modelling the phenomena occurring in Nature, they help in optimization, simulation, modelling, design and prediction purposes in science, medicine, technology, and everyday life. They can be adapted to the given task, be joined with other ones (this leads to combined or hybrid methods), and can work in parallel on many processors. The uses of GAs reported in literature represent a wide variety of approaches and led to solving of numerous computational problems of high complexity. In materials science and related fields of science and technology the GAs open possibilities for materials design, studies of their properties, or production at industrial scale. Here, the recent use of GAs in various domains connected to materials science, solid state physics and chemistry, crystallography, biology, and engineering is reviewed. The listed examples taken from recent literature show how broad the use of these methods is. Emphasis on description of particular results is put in order to direct the reader's attention to valuable new applications as well as interesting or promising ways of solving specific tasks. Trends in method development and application-field extensions as well as some possible future implications are briefly discussed.