CAJ | 학술논문

针对动态路径诱导中寻优算法收敛速度慢,易陷入局部最优解的不足,提出了一种改进的量子蚁群算法( IQA-CA). 首先,建立了考虑交叉口和路段耗费的动态路网模型,并建立了时间最优路径模型. 借鉴量子蚁群算法的寻优策略,改进的量子蚁群算法通过将量子比特相位取值范围缩小的方法,提高概率幅的密度;采用Hadamard门变异机制,实现量子比特概率幅值的位置和大小的变化,扩大了种群多样性,增加了全局最优解搜索的概率. 将IQACA算法应用到实际路网的动态路径诱导中,并与蚁群算法、量子蚁群算法进行对比分析,实验结果表明,改进的IQACA算法适用于求解时间最优路径问题,不仅具有很好的收敛性能还能够较快的得出时间最优路径.
침대동태로경유도중심우산법수렴속도만,역함입국부최우해적불족,제출료일충개진적양자의군산법( IQA-CA). 수선,건립료고필교차구화로단모비적동태로망모형,병건립료시간최우로경모형. 차감양자의군산법적심우책략,개진적양자의군산법통과장양자비특상위취치범위축소적방법,제고개솔폭적밀도;채용Hadamard문변이궤제,실현양자비특개솔폭치적위치화대소적변화,확대료충군다양성,증가료전국최우해수색적개솔. 장IQACA산법응용도실제로망적동태로경유도중,병여의군산법、양자의군산법진행대비분석,실험결과표명,개진적IQACA산법괄용우구해시간최우로경문제,불부구유흔호적수렴성능환능구교쾌적득출시간최우로경.
To solve the problems of slow convergence speed, easily falling into local optimal solution in optimization algorithm of dynamic route guidance, an improved quantum ant colony algorithm ( IQACA) is proposed in this pa-per. Firstly, a dynamic road network model considering road intersection and road-consuming and a time optimal path model are established. Taking the quantum ant colony optimization algorithm strategy as reference, the im-proved quantum ant colony algorithm increases the probability amplitude density by narrowing the range of the qubit phase. Hadamard gate mutation mechanism is introduced to make the changes of the qubit probability amplitude' s position and size, which expands population diversity and increases the searching probability of globally optimal so-lution. IQACA is applied to the dynamic route guidance of an actual road network, and is analyzed comparing with the ant-colony algorithm and quantum ant colony algorithm. The simulation shows that IQACA is applicable to sol-ving the problem of time optimal path, which not only has good convergence performance but also obtains the time optimal route quickly.