CAJ | 학술논문

量子菌群算法是将量子计算与菌群觅食优化算法相融合而得到的一种量子智能算法，但该算法存在鲁棒性比较差和寻优时间比较长的缺陷。为解决该问题，本文设计了一种旋转相位自适应调整的量子旋转门，并用其完成细菌的趋化操作，提出了一种自适应相位旋转的量子菌群算法。通过16个不同类型的标准测试函数对其优化性能进行研究，统计结果表明该算法在低维时，对于多种种类的测试函数，在收敛精度和稳定性上都要优于改进前的量子菌群算法，且优化结果要明显优于经典的菌群觅食优化算法和量子遗传算法。进一步研究表明，在达到指定收敛精度的情况下，该算法的平均收敛概率是最高的，平均运行时间和平均迭代步数是最短的。而在高维情况下，该算法则对碗状和碟状类型的测试函数比较适用。
양자균군산법시장양자계산여균군멱식우화산법상융합이득도적일충양자지능산법，단해산법존재로봉성비교차화심우시간비교장적결함。위해결해문제，본문설계료일충선전상위자괄응조정적양자선전문，병용기완성세균적추화조작，제출료일충자괄응상위선전적양자균군산법。통과16개불동류형적표준측시함수대기우화성능진행연구，통계결과표명해산법재저유시，대우다충충류적측시함수，재수렴정도화은정성상도요우우개진전적양자균군산법，차우화결과요명현우우경전적균군멱식우화산법화양자유전산법。진일보연구표명，재체도지정수렴정도적정황하，해산법적평균수렴개솔시최고적，평균운행시간화평균질대보수시최단적。이재고유정황하，해산법칙대완상화설상류형적측시함수비교괄용。
Quantum bacterial foraging optimization algorithm is an quantum intelligence algorithm which is based on the concept of quantum computing and bacteria foraging optimization algorithm.However,this algorithm exists the defects of poor robustness and the problem of long running time in optimization.To solve these problems,this paper designs a quan-tum rotation gate which has a adaptive phase rotation.Using this rotation gate simulating the bacterial chemotaxis operation, this paper proposes a quantum foraging algorithm based on adaptive phase rotation.To test the new algorithm’s optimization performance,a research based on sixteen benchmark functions is conducted.The results indicate that in the situation of low dimension,the new AQBFO algorithm shows better results than QBFO in convergence precision and stability,say nothing of QGA and BFO.Further research shows that,average convergence probability of the proposed algorithm is the highest and the average running time and average running steps are the shortest among the four algorithms when reach the specified con-vergence precision.While in the situation of high dimension,this algorithm is suitable for bowl shape and plate shape benchmark functions.