基于蚁群算法的管道规划改进方法探究

Research on improving pipeline planning method with ant colony algorithm

传统蚁群在区域规模较大时收敛速度逐渐减慢,会出现效率低、精准度下降、局部最优解概率高等弊端。文章针对传统蚁群算法出现的这些问题进行改进,提出一种双向蚁群算法,构造解空间时可以有效的降低数据规模。双向蚁群算法起点和终点并行计算,使得蚁群算法的搜索效率得到了极大的提高,并且可避免算法陷入局部最优解,提高了结果的有效性和准确性。

When the area scale of traditional ant colony is large,the convergence speed gradually slows down,resulting in the disadvantages of low efficiency,stagnation and high probability of local optimal solution.Aiming at the problems of traditional ant colony algorithm,this paper proposes a bidirectional ant colony algorithm,which can effectively reduce the size of data when constructing solution space.The parallel computation of the start and end points of the bidirectional ant colony algorithm greatly improves the search efficiency of ant colony algorithm,avoids the algorithm falling into the local optimal solution,and improves the accuracy of the results.