Genetic algorithms (GAs) are a helpful tool in optimization, simulation, modelling, design,
and prediction purposes in various domains of science including materials science …

Genetic algorithm is employed for optimum designing of patient specific dental implants with
varying dimension and porosity. It is generally recommended that, the micro strain at the …

The current state of the art of materials research using multi-objective genetic and
evolutionary algorithms is briefly presented with critical analyses. The basic concepts of …

Liquid metal (LM) is increasingly employed as a conductive filler in soft and flexible
elastomer composites owing to its favorable conductivity and liquid fluidity. However, the …

Artificial neural network model is developed for the prediction of phase transformation of
steel from austenite, and thus construction of the continuous cooling transformation (CCT) …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

With the rapid growth of laser applications and the introduction of high efficiency lasers (eg
fiber lasers), laser material processing has gained increasing importance in a variety of …

Several statistical techniques are used for the design of materials through extraction of
knowledge from existing data banks. These approaches are getting more attention with the …

The purpose of current investigation is to develop a robust intelligent framework to achieve
efficient and reliable operating process parameters for laser solid freeform fabrication (LSFF) …

Imprecise knowledge on the composition–processing–microstructure–property correlation of
titanium alloys combined with experimental data are used for developing rule based models …