自适应信息遗传算法在路面模量反算中的应用和稳健性研究

发布时间：2018-11-03 09:26

【摘要】：路基作为路面结构的基础支撑体,实际路基工程所发生的路面损坏基本上是基于路基稳定性差、强度较低,受到外部载荷作用而产生过量形变造成。主要是针对路面模量反算过程中所获得的目标函数在最优值呈现出一个狭长平坦区的特征,提出了一个基于模量反算的自适应信息遗传算法,并对新算法在路面模量反算中的稳健性进行了理论和实践对比分析。首次采用了以信息量来确定是否执行细分模量解空间的机制,有效的缩小了后期反算空间,同时,采用改进行的实数交叉算子,提高了新算法后期搜索能力,通过比较实际FWD实际检测结果与新算法的反算结果表明:自适应信息遗传算法有效的降低了传统遗传算法的复杂度,提高了求解效率,有效的保证了新算法在工程实际应用中的稳健性。
[Abstract]:As the foundation support of the pavement structure, the pavement damage in the actual subgrade engineering is basically caused by the poor stability of the subgrade, low strength and excessive deformation caused by the external load. This paper presents an adaptive information genetic algorithm (AGA) based on the inverse calculation of the modulus of the pavement, aiming at the fact that the objective function obtained in the course of the back calculation of the pavement modulus presents a long and narrow flat region at the optimal value. The robustness of the new algorithm in the back calculation of pavement modulus is compared in theory and practice. The mechanism of determining whether the subdivision modulus solution space is executed by the amount of information is adopted for the first time, which effectively reduces the later inverse computation space. At the same time, the improved real number crossover operator is used to improve the search ability of the new algorithm. By comparing the actual FWD detection results with the inverse calculation results of the new algorithm, it is shown that the adaptive information genetic algorithm can effectively reduce the complexity of the traditional genetic algorithm and improve the efficiency of the solution. It effectively guarantees the robustness of the new algorithm in engineering practice.
【作者单位】：通辽市扎鲁特旗公路管理段;
【分类号】：U416.2

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