A STUDY ON GENETIC ALGORITHM AND ITS APPLICATIONS
The use of genetic algorithms in many fields is demonstrated in this study along with how they may be integrated with a number of other approaches to arrive at the best possible solution and speed up information retrieval systems.
Abstract
We need a way to differentiate the best and worse solutions in order to get the best outcomes. A statistical model or simulation could be the metric, or it could be a subjective one where we favor better results over worse ones. In addition, the fitness function chooses a top solution for a particular issue, which is then used by the GA to direct the evolution of other top solutions. The use of genetic algorithms in many fields is demonstrated in this study along with how they may be integrated with a number of other approaches to arrive at the best possible solution and speed up information retrieval systems.