A quantum genetic algorithm with quantum crossover and mutation operations
This work addresses a bottleneck in quantum computing for optimization problems, though it appears incremental as it builds on existing quantum genetic algorithms.
The paper tackles the lack of a quantum crossover operation in evolutionary quantum computing by introducing a novel quantum genetic algorithm with parallel quantum crossover and mutation, achieving a quadratic speedup in runtime per generation.
In the context of evolutionary quantum computing in the literal meaning, a quantum crossover operation has not been introduced so far. Here, we introduce a novel quantum genetic algorithm which has a quantum crossover procedure performing crossovers among all chromosomes in parallel for each generation. A complexity analysis shows that a quadratic speedup is achieved over its classical counterpart in the dominant factor of the run time to handle each generation.