摘要
考虑到遗传算法的天然并行性和集群计算的高速并行性,提出了基于主从式并行遗传算法的岩土力学参数反分析方法。采用实数编码方法,缩短了个体编码的长度,减少了搜索空间;采用动态任务分配方案,可以避免处理器效率的不均衡;采取"松耦合"的方法将主从式并行遗传算法与FLAC程序进行耦合。基于C+MPI语言编写了反分析程序,并用标准弹性问题对程序进行了测试。测试结果表明,主从式并行遗传算法不仅能够准确地对岩土力学参数进行反分析,而且随着问题规模的增大可以得到接近线性的加速比。因此,针对适应度评价计算量大的岩土工程反分析问题,采用基于主从式并行遗传算法的岩土力学参数反分析方法,既保证了反分析的求解精度,又提高了反分析速度,满足工程上对于反分析的及时性需求,具有较强的应用价值。
By combining the inherent parallelism of genetic algorithm with the high-speed parallelism of cluster system, a back analysis method of geomechanical parameters based on a master-slave parallel genetic algorithm is presented. Several improved methods are used： real code is used to shorten the length of individual code and reduce the searching scale; dynamic task allocation is used to avoid idle resources of some processors; loose coupling method is used to couple a master-slave parallel genetic algorithm with FLAC. Besides theoretical analysis, the back analysis program is compiled in C and MPI （Message Passing Interface）, and it is also tested by a standard elastic problem. The test results indicate that the back analysis program can achieve high precision and approach linear speedup along with the increase of model scale. Therefore, this back analysis method is applicable and propagable, which can satisfy the timeliness of engineering.
出处
《工程力学》
EI
CSCD
北大核心
2010年第10期21-26,共6页
Engineering Mechanics
基金
国家自然科学基金委员会
二滩水电开发有限责任公司雅砻江水电开发联合研究基金项目(50539090)
关键词
岩土力学
反分析
主从式并行遗传算法
MPI
岩土参数
rock and soil mechanics
back analysis
master-slave parallel genetic algorithm
MPI
geomechanical parameters
