基于遗传算法的物流中心区域布置技术

对物流中心进行全参数化研究。充分考虑了区域形状,通道等实际因素,采用遗传算法解决区域布置问题,使布置结果更具实用性。     

基于粒子群优化的模糊聚类分析

基于求解实优化问题时,粒子群优化算法优于遗传算法。在基于遗传算法的模糊C均值聚类算法基础上,给出了基于粒子群的模糊C均值聚类算法,试验结果表明:该算法克服了传统的模糊C均值聚类算法的缺陷,同时在收敛速度方面明显优于基于遗传算法的模糊C均值聚类算法。     

一种基于佳点集遗传算法的物流配送网络优化

首先根据实际问题分析了物流配送网络优化模型的各个关键组成部分,包括优化目标、决策变量和约束条件,并针对目前物流配送网络优化算法中存在的一些问题提出了一种新的算法,其核心是佳点集遗传算法。该算法编码采用prufer num ber结构,变异和交叉概率自适应选择。     

改进遗传算法在电力系统无功优化中的应用

针对常规遗传算法（GA）的不足,提出了一种改进搜索策略的遗传算法,采取了以下改进措施：在遗传迭代中,根据种群进化过程的个体的适应值大小,对群体进行分级,对级别高的个体进行小范围的搜索,对级别低的个体在大范围内进行搜索,保证群体的多样性的同时,又留住了优良个体。将改进的遗传算法应用于电力系统无功优化,并与常规遗传算法进行了比较,结果表明改进算法在计算速度、收敛性和全局最优搜索能力都有提高。     

泾河年径流量BP神经网络模型研究

以1957—2000年的实测降水序列和泾河年径流量序列为研究对象,利用EMD法和GA建立了泾河年径流量的BP神经网络模型。分析结果表明:泾河流域年降水量变化可能存在准2～3、5～7、10～13、18～22 a的周期;基于EMD的年径流量BP神经网络模型预测值的相对误差为-4.71%～8.21%,基于GA的年径流量BP神经网络模型预测值的相对误差为2.25%～12.22%。     

基于内容相似性的个性化推荐系统的应用

推荐系统应用于远程教育平台中，有助于学生学习。推荐系统具有在线和离线推荐两部分，在线推荐使用最近邻居完成，离线推荐采用基于语义相似的推荐算法，利用信息内容和用户兴趣的相似性来分析数据仓库中相关数据针对用户兴趣模型找到相似文档进行推荐。     

Determining Hydraulic Characteristics of Production Wells using Genetic Algorithm

Proper well management requires the determination of characteristic hydraulic parameters of production wells such as well loss coefficient (C) and aquifer loss coefficient (B), which are conventionally determined by the graphical analysis ofstep-drawdowntest data. However, in the present study, the efficacy of a non-conventional optimization technique called Genetic Algorithm (GA), which ensures near-optimal or optimal solutions, is assessedin determining well parameters from step-drawdown test data. Computer programs were developed to optimize the well parametersby GA technique for two cases: (i) optimization of B and C only, and (ii) optimization of B, C and p (exponent) as well as to evaluate the well condition. The reliability and robustness of the developed computer programs were tested usingnine sets of published and unpublished step-drawdown data from varying hydrogeologic conditions. The well parameters obtained by the GA technique were compared with those obtained by the conventional graphical method in terms of root mean square error(RMSE) and visual inspection. It was revealed that the GA technique yielded more reliable well parameters with significantlylow values of RMSE for almost all the datasets, especially in caseof three-variable optimization. The optimal values of the parametersB, C and p for the nine datasets were found to range from 0.382 to 2.292 min m^-2, 0.091 to 3.262, and 1.8 to 3.6, respectively. Because of a wide variation of p, the GA techniqueresulted in considerably different but dependable and robust well parameters as well as well specific capacity and well efficiency compared to the graphical method. The condition of three wells was found to be good, one well bad and that of the remaining five wells satisfactory. The performance evaluation of the developed GA code indicated that a proper selection of generation number and population size is essential to ensure efficient optimization. Furthermore,a sensitivity analysis of the obtained optimal parameters demonstrated that the GA technique resulted in a unique set ofthe parameters for all the nine datasets. It is concluded thatthe GA technique is an effective and reliable numerical tool for determining the characteristic hydraulic parameters of production wells.     

遗传算法在水库(群)优化调度研究中的应用综述

介绍了遗传算法在水库(群)优化调度中的应用背景及算法的收敛性,讨论了水库(群)优化调度中遗传算法的基本应用步骤以及存在的问题,给出了算法的各种改进方法,并对遗传算法的应用前景进行了展望.     

基于GA优化的地下水水质评价模型的应用

在设定了地下水各污染物的"基准"浓度情况下,用污染物的实测浓度相对值替代水质污染损害率公式中的浓度监测值,采用遗传算法(GA)对公式中的参数优化,得到了38项指标都适用的水质污染损害率和污染损害指数公式,提出用广义模糊对比法对污染损害分指数进行赋权的新方法,计算水质综合污染损害指数。利用该法对河池市4个水厂的地下水水源进行水质综合评价分析,取得了较好的效果。     

基于MATLAB 7.0的GA工具箱在渡槽优化设计中的应用

针对工程优化问题中的多变量、复杂非线性约束条件,运用GA工具箱,对某渡槽结构进行优化,得出了令人满意的优化结果。研究表明,遗传算法工具箱使用简单方便,且能根据不同的优化指标、计算精度寻找出最佳结果,充分体现了遗传算法的全局搜索性能。本优化方法具有计算可靠,快捷高效和图形结果可视化等特点,并具有广阔的应用前景。