In the fields of engineering and data sciences, the optimization problems arise on regular
basis. With the progress in the field of scientific computing and research, the optimization is …

Genetic Algorithm (GA) is one of the most well-regarded evolutionary algorithms in the
history. This algorithm mimics Darwinian theory of survival of the fittest in nature. This …

It was proved that genetic algorithms are the most powerful unbiased optimization
techniques for sampling a large solution space. Because of unbiased stochastic sampling …

In this research, we investigate the application of machine learning techniques to
optimization problems and propose a novel integration between metaheuristics and …

In order to obtain best solutions, we need a measure for differentiating best solutions from
worst solutions. The measure could be an objective one that is a statistical model or a …

In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic
algorithms of great interest in research community are selected for analysis. This review will …

Genetic Algorithm (GA) may be attributed as method for optimizing the search tool for difficult
problems based on genetics selection principle. In additions to Optimization it also serves …

A great wealth of information is hidden amid medical research data that in some cases
cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature …

This paper provides an introduction of Genetic Algorithm, its basic functionality. The basic
functionality of Genetic Algorithm include various steps such as selection, crossover …

The genetic algorithm (GA) is a search heuristic that is routinely used to generate useful
solutions to optimization and search problems. It generates solutions to optimization …