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It was considered as a kind of TSP and solved inversely in order to detect a interference easily. GA have been used successfully to solve continuous functional optimization problems, in which crossover operation typically involves only exchanging randomly selected gene of chromosome between two parents to create two children genotypes. However, these genetic operators are not suitable for routing type problems, because an optimal ordering of a list of objects must be found in order to solve the problem. Furthermore, often the selection of operations requires a deep insight into the nature of the specific problem and operations are not portable to real-problems in themselves. 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