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 simulation, or it can be a subjective one where we choose better solutions over worst ones. Apart from this the fitness function determines a best solution for a given problem, which is subsequently used by the GA to guide the evolution of best solutions. This paper shows how GA is combined with various other methods and technique to derive optimal solution, increase the computation time of retrieval system the applications of genetic algorithms in various fields.

Genetic Algorithm; Optimal Solution; Fitness function

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