量子人工鱼群算法  

Quantum Artificial Fish School Algorithm

作　　者：陈晓峰[1] 宋杰[1] 

机构地区：[1]东北大学软件学院,辽宁沈阳110819

出　　处：《东北大学学报（自然科学版）》2012年第12期1710-1713,共4页Journal of Northeastern University(Natural Science)

基　　金：辽宁省自然科学基金资助项目(200102059);国家自然科学基金资助项目(61173028)

摘　　要：融合量子计算与智能优化的新型高效优化算法层出不穷,成为现在优化算法研究的主流.为此,将量子计算引入到人工鱼群算法中,提出一种新型的量子进化算法———量子人工鱼群算法.该算法用量子计算的方法重新描述了人工鱼的行为,用量子比特对人工鱼进行编码,用量子旋转门实现人工鱼的更新操作,用量子非门进行人工鱼变异,从而实现了目标的优化求解.并分别以函数极值和TSP问题为例进行了仿真,验证了算法的有效性.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.

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 

分 类 号：TP301.418[自动化与计算机技术—计算机系统结构]