摘要
蚁群算法是一种新型的启发式模拟进化算法,为求解各种复杂的组合问题提供了一种新的思路。虽然蚂蚁个体没有智能,但群体蚂蚁可以通过信息素(pheromone)进行互相交流进而协调工作。自从Marco Dorigo根据蚂蚁觅食的过程,首次提出了蚁群算法并且应用于求解最短路径问题以来,针对蚁群算法的研究一直都没有停止。通过对信息素更新策略、局部搜索算法、随机选择概率三个方面的改进,提高算法的全局最优搜索能力和收敛性。实验结果表明,改进算法有较好的性能。
Ant colony algorithm is a novel heuristic simulated evolutionary algorithm,provides a new idea for solving complex problems of combination.Although there is no intelligent individual ant,but groups of ants can be pheromones（pheromone） for further coordination of the exchange.Since the ants foraging Marco Dorigo under the process of the ant colony algorithm was first proposed and applied to solve the shortest path problem,for the ant colony algorithm has not stopped.Based on the pheromone updating strategy,local search algorithm,the probability of randomly selected three areas to improve,improve the algorithm＇s global search ability and convergence of optimal.Experimental results show that the improved algorithm has better performance.
出处
《计算机技术与发展》
2011年第7期202-205,共4页
Computer Technology and Development
基金
国家自然科学基金项目(60970004)
山东省研究生教育创新计划资助项目(SDYY10059)
