岩土工程学报Issue(7)：1252-1261,10.DOI:10.11779/CJGE201407009
基于并行改进遗传算法的三维电阻率反演方法
3D resistivity inversion using improved parallel genetic algorithm
摘要
Abstract
The low calculation efficiency of the genetic algorithm (GA) method is an obstacle to 3D resistivity inversion. Moreover, some improved methods which are time-consuming but beneficial for the inversion effect and the search efficiency can not be used in GA due to their low calculation efficiencies. To solve the above problems, a multi-level master-slave parallel computing strategy for GA is put forward based on the natural characteristics of parallel computing. Through this improvement, a generating method for strictly uniform initial population is proposed, with which the initial generation can be closer to the optimal solution. A random-ratio arithmetical crossover algorithm is proposed based on the differences of fitness values between the cross-individuals, which can keep genetic competition advantages of the better individual. Then the joint mutation algorithm is presented, which is the combination of the traditional random mutation algorithm and the deterministic search optimization algorithm in the linear inversion. It can maintain the randomness of the mutation and optimize the mutation direction. Eventually a 3D resistivity inversion using an improved parallelized GA is formed. The performance of the improved parallel GA is evaluated in synthetic and practical cases. The examples illustrate that the improved parallel GA can enhance the calculation efficiency significantly and has obvious advantages in searching the optimal solution, suppressing the false anomaly and obtaining high-quality inversion results. The improved parallel GA provides an effective way for 3D resistivity inversion imaging in practical projects.关键词
三维电阻率反演成像/并行改进遗传算法/多重主从并行算法/比例随机交叉算法/混合变异算法Key words
3D resistivity inversion imaging/improved parallel genetic algorithm/multi-level master-slave parallel computing strategy/random ratio arithmetical crossover algorithm/joint mutation algorithm分类
矿业与冶金引用本文复制引用
刘斌,王传武,杨为民,李术才,聂利超,宋杰..基于并行改进遗传算法的三维电阻率反演方法[J].岩土工程学报,2014,(7):1252-1261,10.基金项目
国家重点基础研究发展计划（973计划）（2013CB036002，2014CB046901）；国家重大科研仪器设备研制专项（51327802）；国家自然科学基金重点项目（51139004）；国家自然科学基金青年项目（41102183）；高等学校博士学科点专项科研基金项目（新教师类）(20110131120070) （20110131120070）
