文档介绍：J I A N G S U U N I V E R S I T Y
本科毕业论文
基于蚁群算法路由选择可视化动态模拟
Visul Simulation of Routing Selsect based on Ant Colony Algorithms
学院名称: 计算机学院
专业班级: JW012班
学生姓名: 周健
指导教师姓名: 朱娜
指导教师职称: 副教授
2005年 6月
摘要
路由选择是一种基于网络层的协议,而所有流行的网络层路由选择协议都是基于以下两种典型的分布式算法之一:距离向量路由算法和链路状态路由算法。组合优化问题是人们在工程技术、科学研究和经济管理等众多领域经常遇到的问题,其中许多问题如旅行商问题、0-1背包问题、图着色问题、装箱问题等,都被证明为NP-困难问题。用确定性的优化算法求NP完全问题的最优解,其计算时间使人难以忍受或因问题的高难度而使其计算时间随问题规模的增加以指数速度延长。用近似算法如启发式算法求解得到的近似解不能保证其可行性和最优性,甚至无法知道所得解同最优解的近似程度。因而在求解大规模组合优化问题时,传统的优化算法就显得无能为力了。在过去的10多年,蚁群算法(ACO)的研究和应用取得了很大的进展,大量结果证明了算法的有效性和在某些领域的优势。蚁群算法是一种新型的模拟进化算法, 研究表明该算法具有并行性, 鲁棒性等优良性质。本文阐述了蚁群算法的原理,详细的说明了蚂蚁算法中各个功能模块,并介绍了该算法在理论和实际问题中的应用, 并对其前景进行了展望。
关键词: 蚁群算法信息素仿真
Abstract
Whether it is one based on agreement for route not to choose, and all route that prevail choose agreement on the basis of the following two typical distributed algorithm one of. Is it optimize problem people in engineering , scientific research , economic management numerous problem that field run into often to make up, among them a lot of question if knapsack issue , issue of businessman in the travel industry and of TSP , pursue painted question , case issue ,etc., proved as 6WF difficult problem. Ask the solving optimumly of plete problem with the deterministic optimization algorithm, calculation its time make people to be insufferable making their calculation time up to increase , issue of scale lengthen so as to index speed because the question is highly difficult. If heuristic algorithm is it solve receive approximate solution can the assurance feasibility and getting optimum their to ask with algorithm of similar toing, it is even unable to know es and solve and solve optimumly to be similar to the degree. Therefore while asking and solving and making the question of optimizing up on a large scale, the traditional optimization algorithm seems powerless . From vectorial route algorithm, algorithm of route and state of chain The researches and applications on ACO algorithm hav