Assistance of Novel Artificial Intelligence in Optimization of Aluminum Matrix Nanocomposite by Genetic Algorithm

作者：Mazahery Ali^*; Shabani Mohsen Ostad

来源：Metallurgical and Materials Transactions A-Physical Metallurgy and Materials Science, 2012, 43A(13): 5279-5285.

DOI：10.1007/s11661-012-1339-6

In this article, a genetic algorithm (GA) is used to predict the mechanical properties and to optimize the process conditions of Al nanocomposites. An artificial intelligence method is also implemented as an assisting tool for engineering tasks of GAs. The principle of the survival of the fittest is applied to produce successively superior approximations to a solution. A population of points at each iteration is generated. The population approaches an optimal solution. The next population by computations that involve random choices is selected. The optimal volume percentage of SiC, cooling rate, and temperature gradient are computed to be 2.84 pct, 283 K/s (10 A degrees C/s), 1273 K/m (1000 A degrees C/m), respectively.

• 出版日期2012-12