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

被引:61
作者
Paszkowicz, Wojciech [1 ]
机构
[1] Polish Acad Sci, Inst Phys, Al Lotnikow 32-46, PL-02668 Warsaw, Poland
关键词
Algorithm; Application; Artificial; Computing; Engineering; Evolution; Genetic; Global; Intelligence; Materials; Modeling; Optimization; Parallel; Prediction; Science; ARTIFICIAL NEURAL-NETWORK; CRYSTAL-STRUCTURE PREDICTION; METAL-ORGANIC FRAMEWORKS; MULTIOBJECTIVE OPTIMIZATION; GLOBAL OPTIMIZATION; OPTIMAL-DESIGN; PARAMETERS IDENTIFICATION; EVOLUTIONARY ALGORITHMS; ANTIREFLECTION COATINGS; DIFFERENTIAL EVOLUTION;
D O I
10.1080/10426914.2012.746707
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Genetic algorithms (GAs) are a helpful tool in optimization, simulation, modelling, design, and prediction purposes in various domains of science including materials science, medicine, technology, economy, industry, environment protection, etc. Reported uses of GAs led to solving of numerous complex computational tasks. In materials science and related fields of science and technology, GAs are routinely used for materials modeling and design, for optimization of material properties, the method is also useful in organizing the material or device production at the industrial scale. Here, the most recent (years 2008-2012) applications of GAs in materials science and in related fields (solid state physics and chemistry, crystallography, production, and engineering) are reviewed. The representative examples selected from recent literature show how broad is the usefulness of this computational method.
引用
收藏
页码:708 / 725
页数:18
相关论文
共 208 条
[1]  
Affenzeller M, 2009, NUMER INSIGHT, pXXV
[2]   Analysing blast furnace data using evolutionary neural network and multiobjective genetic algorithms [J].
Agarwal, A. ;
Tewary, U. ;
Pettersson, F. ;
Das, S. ;
Saxen, H. ;
Chakraborti, N. .
IRONMAKING & STEELMAKING, 2010, 37 (05) :353-359
[3]  
Alander J.T., AUTOMATION U VAASA R, V94-1-MSE
[4]  
Alander J.T., 941X U VAAS
[5]   Optimization of all-garnet magneto-optical magnetic field sensors with genetic algorithm [J].
Alisafaee, Hossein ;
Ghanaatshoar, Majid .
APPLIED OPTICS, 2012, 51 (21) :5144-5148
[6]   Prediction of Structure and Properties of Boron-Based Covalent Organic Frameworks by a First-Principles Derived Force Field [J].
Amirjalayer, Saeed ;
Snurr, Randall Q. ;
Schmid, Rochus .
JOURNAL OF PHYSICAL CHEMISTRY C, 2012, 116 (07) :4921-4929
[7]   Exploring Network Topologies of Copper Paddle Wheel Based Metal-Organic Frameworks with a First-Principles Derived Force Field [J].
Amirjalayer, Saeed ;
Tafipolsky, Maxim ;
Schmid, Rochus .
JOURNAL OF PHYSICAL CHEMISTRY C, 2011, 115 (31) :15133-15139
[8]  
[Anonymous], 1999, COMPUTATIONAL MAT SC
[9]  
[Anonymous], 2011, J TELECOMMUNICATIONS
[10]  
Arabas J., 2004, Wyklady Z Algorytmow Ewolucyjnych