滑坡治理方案客观自主式智能优化求解算法

Objective Self-determined Intelligent Optimization Algorithm for Selecting Landslide Treatment Scheme

为合理评价并优选滑坡治理方案,采用位置加权向量规划模型和蛙跳算法,研究滑坡治理方案客观自主式智能优化求解算法。使用该方法时,首先确定评价指标的绝对优势度和相对优势度,以此为诱导分量,按照IOWA算子的思想将各评价对象的评价指标重新排序;然后,利用蛙跳算法优化求解评价指标的位置加权向量和评价值向量;最后,对评价值矩阵进行集结,通过向量夹角和最小法求得各评价对象的最优评价值向量。实例计算和对比分析结果表明,该方法与其他优选理论计算结果一致。

To reasonably evaluate and select landslide treatment schemes, an objective self-determined intelligent optimization algorithm was proposed based on the programming model of position weighted vector and leapfrog algorithm. Firstly, the absolute dominance and relative dominance were determined and they were taken as induced components. The evaluation indexes were rearranged in accordance with the ideology of the IOWA operator. Secondly, the position weighted vectors and evaluation values were solved by leapfrog algorithm. Finally, an evaluation value matrix was constituted, and the optimal evaluation vectors were solved by the method of the minimum sum of the vector angles. It is verified that the results calculated by this method are consistent with those obtained according to other optimal selection theories, this method may provide a new way for selecting landslide treatment schemes.