论文部分内容阅读
蚁群算法于上世纪末提出,是继遗传算法之后的一种启发式算法,用于解决组合优化问题。它借鉴蚂蚁通过自组织的协作能力而产生的群体智慧来解决组合优化问题。ACO算法的特点在于使用正反馈,在较优的解的路径下,留下较多的信息激素,信息素会吸引更多蚂蚁走这条路径,这个过程中,会引导整个系统向最优解的方向迈进。蚁群算法可以用来解决一些尚未找到有效算法的问题,而且蚁群算法还是元启发式算法(Metaheuristic),是一种算法框架,可以在其基本思想上针对不同问题做改进从而应用到不同问题上去。
Ant colony algorithm proposed in the end of last century is a heuristic algorithm after genetic algorithm, which is used to solve the combinatorial optimization problem. It draws on the collective wisdom of ants through self-organizing collaborative capabilities to solve combinatorial optimization problems. ACO algorithm is characterized by the use of positive feedback, in the optimal solution path, leaving more information hormones, pheromone will attract more ants take this path, this process will guide the entire system to the optimal solution The direction of progress. Ant colony algorithm can be used to solve some problems not found effective algorithm, and ant colony algorithm is meta-heuristic (Metaheuristic), is an algorithm framework that can be improved in its basic ideas for different problems to be applied to different problems Go up.