摘要
从最短路径问题的研究背景、最短路径问题概述、求解最短路径问题的自适应路由遗传优化算法的设计及其实现等方面提出了一种新的求解最短路径问题的自适应路由遗传优化算法,实验仿真比较了该算法与Dijkstra算法的路由过程、算法的收敛性和执行的效率,结果初步证明该算法高效可行,尤其适合于大规模网络.
Based on the research background and an overview of shortest path problem, a new serf-adaptive routing genetic optimization algorithm for this problem is proposed in terms of design and implementation. An experimental simulation is conducted to compare this algorithm with Dijkstra algorithm in routing process, convergence, and execution efficiency. The preliminary results show that the algorithm is highly efficient and feasible, particularly applicable to large-scale networks.
出处
《南京工程学院学报（自然科学版）》
2012年第2期29-33,共5页
Journal of Nanjing Institute of Technology(Natural Science Edition)
关键词
最短路径问题
自适应
遗传算法
shortest path problem
self-adaptive
genetic algorithm
