关键词: 量子计算, 人工鱼群算法, 量子人工鱼群算法, 函数极值, TSP问题

Abstract: Many newly-proposed algorithms, which combine both quantum computing and intelligent optimization, are becoming mainstream of optimization algorithm studies. For introducing quantum computing to the fish school algorithm, a new evolution algorithm, named as quantum artificial fish school algorithm, was proposed. The actions of fish school were re-described through quantum computing. The artificial fishes were encoded by quantum bits. The update of artificial fishes was implemented by quantum rotated gate. Mutation of fishes was performed by quantum negation gate, and finally the optimized solution of target functions was retrieved. The algorithm was simulated by extremum problem and TSP problem and was proved to be effective and efficient.