CAJ | 학술논문

蚁群算法是一种求解最优路径的常用算法，其利用自然界中蚁群的活动规律和正反馈原理。动态的蚁群算法针对基本蚁群算法存在的问题和缺点进行改进，采用动态参数因子，可以有效避免搜索的局部最优和进化停滞现象，并且能够提高搜索效率。通过实验结果对比，该算法在求解最短路径方面具有更高的精确度，为今后的搜救问题提供了一种高效实用的参考方法。
의군산법시일충구해최우로경적상용산법，기이용자연계중의군적활동규률화정반궤원리。동태적의군산법침대기본의군산법존재적문제화결점진행개진，채용동태삼수인자，가이유효피면수색적국부최우화진화정체현상，병차능구제고수색효솔。통과실험결과대비，해산법재구해최단로경방면구유경고적정학도，위금후적수구문제제공료일충고효실용적삼고방법。
Ant colony algorithm,using the positive feedback principle and the activity rhythm of ant colony in nature,is one of commonly used algorithms for finding the optimal path. Dynamic ant colony algorithm has improved the problems and dis-advantages existing in basic ant colony algorithm,the local optimal search and evolutionary stagnation phenomenon can be effec-tively avoided by using dynamic parameter factors,and the search efficiency can be improved. By comparison with the experi-mental results,the algorithm has higher accuracy in finding the shortest path,which provides an efficient and practical reference method for the future search problems.