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Genetic algorithms are metaheuristic algorithms,
which mean that it generates useful solutions to solve NP-hard
optimization problems in moderate execution times. However,
Genetic algorithms usually require more computation power
than other heuristic approaches do. Due to the complexity of
problem such as TSP, finding a good solution with traditional
ways needs a huge computational power (in term of processing
power and memory usage) as well as time to solve.