To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （...To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （PERT）, some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm （GA） based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.展开更多
为了保证永磁无刷直流空心轴电机的输出性能和抑制电磁振动,提出了一种基于非线性多元回归的修正代理模型优化方法.首先,通过AE(Audze-Elglajs)准则确定最优空间填充抽样,并采用核主成分分析(Kernel Principal Components Analysis,KPCA...为了保证永磁无刷直流空心轴电机的输出性能和抑制电磁振动,提出了一种基于非线性多元回归的修正代理模型优化方法.首先,通过AE(Audze-Elglajs)准则确定最优空间填充抽样,并采用核主成分分析(Kernel Principal Components Analysis,KPCA)算法筛选出4个主要变量用于构建代理模型;其次,采用非线性多元回归构建代理模型,决定系数R^(2)值均大于0.9,验证了代理模型的精度;最后,采用鲁棒多目标遗传算法求解代理模型,获得了最优定子槽参数.结果表明,通过优化定子槽参数,电机平均转矩降低了1.3%,不影响输出性能,电机空载、额定负载时最大振动加速度分别降低19%和34.5%,有效地降低了电磁振动,验证了优化方法的有效性和可靠性.展开更多
目前,大多数多目标进化算法采用为单目标优化所设计的重组算子.通过证明或实验分析了几个典型的单目标优化重组算子并不适合某些多目标优化问题.提出了基于分解技术和混合高斯模型的多目标优化算法(multiobjective evolutionary algorit...目前,大多数多目标进化算法采用为单目标优化所设计的重组算子.通过证明或实验分析了几个典型的单目标优化重组算子并不适合某些多目标优化问题.提出了基于分解技术和混合高斯模型的多目标优化算法(multiobjective evolutionary algorithm based on decomposition and mixture Gaussian models,简称MOEA/D-MG).该算法首先采用一个改进的混合高斯模型对群体建模并采样产生新个体,然后利用一个贪婪策略来更新群体.针对具有复杂Pareto前沿的多目标优化问题的测试结果表明,对给定的大多数测试题,该算法具有良好的效果.展开更多
基金the National High-Tech. R & D Program for CIMS, China (2003AA413210).
文摘To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning （ERP） implementation, combined with program evaluation and review technique （PERT）, some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm （GA） based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.
文摘为了保证永磁无刷直流空心轴电机的输出性能和抑制电磁振动,提出了一种基于非线性多元回归的修正代理模型优化方法.首先,通过AE(Audze-Elglajs)准则确定最优空间填充抽样,并采用核主成分分析(Kernel Principal Components Analysis,KPCA)算法筛选出4个主要变量用于构建代理模型;其次,采用非线性多元回归构建代理模型,决定系数R^(2)值均大于0.9,验证了代理模型的精度;最后,采用鲁棒多目标遗传算法求解代理模型,获得了最优定子槽参数.结果表明,通过优化定子槽参数,电机平均转矩降低了1.3%,不影响输出性能,电机空载、额定负载时最大振动加速度分别降低19%和34.5%,有效地降低了电磁振动,验证了优化方法的有效性和可靠性.
文摘目前,大多数多目标进化算法采用为单目标优化所设计的重组算子.通过证明或实验分析了几个典型的单目标优化重组算子并不适合某些多目标优化问题.提出了基于分解技术和混合高斯模型的多目标优化算法(multiobjective evolutionary algorithm based on decomposition and mixture Gaussian models,简称MOEA/D-MG).该算法首先采用一个改进的混合高斯模型对群体建模并采样产生新个体,然后利用一个贪婪策略来更新群体.针对具有复杂Pareto前沿的多目标优化问题的测试结果表明,对给定的大多数测试题,该算法具有良好的效果.
