计算机工程与应用Issue(22)：36-39,54,5.DOI:10.3778/j.issn.1002-8331.1305-0165
求解旅行商问题的混合量子蚁群算法
Hybrid Quantum Ant Colony Algorithm for Traveling Salesman Problem
摘要
Abstract
Aiming at the Traveling Salesman Problem based on ant colony optimization which is easy to fall into local optimums and has a slow convergence rate, a hybrid quantum ant colony optimization algorithm is presented. In this algorithm, the pheromone on each path is encoded by a group of quantum bits, the quantum rotation gate and ant’s tour are used to update the pheromone so as to accelerate its convergence speed. To avoid the search falling into local optimum, the new neighborhood exchange strategy is designed to improve solution efficiency. Some cases from the TSP library(TSPLIB)are used to experiment, the results show that the algorithm has rapider convergence speed and higher accuracy than the classical ant colony algorithm.关键词
量子蚁群算法/变换邻域准则/旅行商问题Key words
Quantum Ant Colony Algorithm/neighborhood exchange strategy/Traveling Salesman Problem分类
信息技术与安全科学引用本文复制引用
贾瑞玉,李亚龙,管玉勇..求解旅行商问题的混合量子蚁群算法[J].计算机工程与应用,2013,(22):36-39,54,5.基金项目
安徽省教育厅自然科学研究基金资助重点项目（No.2011A006）。 （）
