Semiclassical genetic algorithm with quantum crossover and mutation operations

Computer Science – Neural and Evolutionary Computing

Scientific paper

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13 pages, no figure, v2: typos corrected, minor modifications in sections 3.5 and 4

Scientific paper

In order for finding a good individual for a given fitness function in the
context of evolutionary computing, we introduce a novel semiclassical quantum
genetic algorithm. It has both of quantum crossover and quantum mutation
procedures unlike conventional quantum genetic algorithms. A complexity
analysis shows a certain improvement over its classical counterpart.

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