%0 Journal Article
%T Solving Traveling Salesman Problem by Chaos Ant Colony Optimization Algorithm<br>解旅行商问题的混沌蚁群算法
%A GAO Shang
%A <br>高尚
%J 系统工程理论与实践
%D 2005
%I 
%X By use of the properties of ergodicity, randomicity, and regularity of chaos, a chaos ant colony optimization (CACO) algorithm is proposed to solve traveling salesman problem. The basic principle of CPSO algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum. Compared with the standard GA and simulated annealing algorithm ,simulation results show that chaos ant colony optimization is a simple and effective algorithm.
%K ant colony algorithm
%K chaos
%K chaos perturbation
%K chaos ant colony optimization algorithm
%K traveling salesman problem<br>蚁群算法
%K 混沌
%K 混沌扰动
%K 混沌蚁群算法
%K 旅行商问题
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=173EE240F4535C37&yid=2DD7160C83D0ACED&vid=C5154311167311FE&iid=9CF7A0430CBB2DFD&sid=8C83C265AD318E34&eid=DBF54A8E2A721A6D&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=16&reference_num=17