Keywords :
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Genetic Algorithm, Optimization, Cross-over, Mutation, RVS, SVS, Encoding in GA
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Abstract :
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Applying mathematics to a problem of the real world mostly means, at first, modeling the problem mathematically, maybe with hard restrictions, idealizations, or simplifications, then solving the mathematical problem, and finally drawing conclusions about the real problem based on the solutions of the mathematical problem. Since about 60 years, a shift of paradigms has taken place in some sense; the opposite way has come into fashion. The point is that the world has done well even in times when nothing about mathematical modeling was known. The one of the alternate ways is evolutionary computation, which encompasses three main components- Evolution strategies, Genetic Algorithms and Evolution programs. One such alternative is to use a GA-based routing algorithm. GA may be used for optimization of searching process for optimum path routing in a network for optimization of both the distance and the congestion problem in a network. The proposed GA structure for the problem at hand is encoded in Matlab.
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