Subrata Datta, Chayanika Garai and Chandrani Das
Genetic Algorithms are search algorithms based on the mechanics of natural selection and natural genetics. They combine survival of the fittest among string structures with a structured yet randomized information exchange to form such an algorithm with some of the innovative flair of human search. In every generation, a new set of artificial creatures (Strings) is created using bits and pieces of the fittest of the old; an occasional new part is tried for good measure. Linear Programming (LP) is the most commonly applied form of constrained optimization. In this paper we proposed an efficient genetic algorithm applied on linear programming problem for find out the Fittest Chromosomes. The experimental performances find out the fittest chromosomes regarding to constraint linear programming problem, so that it gives a better result.
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