The automobile industry is presently focusing on processing of advanced steels with
superior strength–ductility combination and lesser weight as compared to conventional high …

Current trends in the progress of technology demand availability of materials resources
ahead of the advancing fronts of the application areas. During the last couple of decades …

The present work reports on the development of modeling and optimization for micro-electric
discharge machining (μ-EDM) process. Artificial neural network (ANN) is used for analyzing …

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 …

Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are
used in learning and modeling especially with the advent of big data related problems. This …

The accurate prediction of tensile properties has great importance for the service life
assessment and alloy design of RAFM steels. In order to overcome the limitation of …

Data driven models were constructed for the Cu―Zn separation process using Di (2-ethyl
hexyl) phosphoric acid (D2EHPA) as the mobile carrier in a supported liquid membrane. The …

Existing acid leaching data for low-grade manganese ores are modeled using an evolving
neural net. Three distinct cases of leaching in the presence of glucose, sucrose and lactose …

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

This article illustrates an application of response surface methodology (RSM) and genetic
algorithm (GA) for selecting the optimum combination values of drilling parameters affecting …