The petrol truck routing problem is an important part of the petrol supply chain.This study focuses on determining routes for distributing petrol products from a depot to petrol stations with the objective of minimizi...The petrol truck routing problem is an important part of the petrol supply chain.This study focuses on determining routes for distributing petrol products from a depot to petrol stations with the objective of minimizing the total travel cost and the fixed cost required to use the trucks.We propose a mathematical model that considers petrol trucks returning to a depot multiple times and develop a heuristic algorithm based on a local branch-and-bound search with a tabu list and the Metropolis acceptance criterion.In addition,an approach that accelerates the solution process by adding several valid inequalities is presented.In this study,the trucks are homogeneous and have two compartments,and each truck can execute at most three tasks daily.The sales company arranges the transfer amount and the time windows for each station.The performance of the proposed algorithm is evaluated by comparing its results with the optimal results.In addition,a real-world case of routing petrol trucks in Beijing is studied to demonstrate the effectiveness of the proposed approach.展开更多
高斯过程回归(Gaussian process regression,GPR)是一种基于高斯过程的非参数化贝叶斯回归方法,其可以灵活适应不同类型数据,用于建模和预测数据之间的复杂关系,具有拟合能力强、泛化能力好等特点。针对海量用户场景下用户量实时预测问...高斯过程回归(Gaussian process regression,GPR)是一种基于高斯过程的非参数化贝叶斯回归方法,其可以灵活适应不同类型数据,用于建模和预测数据之间的复杂关系,具有拟合能力强、泛化能力好等特点。针对海量用户场景下用户量实时预测问题,提出一种基于GPR的用户量预测优化方法。在滑动窗口方法处理数据的基础上,选择合适的核函数,基于k折交叉验证得到最佳超参数组合以实现GPR模型训练,完成在线用户量的实时预测并进行性能评估。实验结果表明,相比于采用训练集中输出数据方差的50%作为信号噪声估计量的传统方案,所提方法具有较高的预测准确度,并且在测试集均方根误差(root mean square,RMS)、平均绝对误差(mean absolute error,MAE)、平均偏差(mean bias error,MBE)和决定系数R 2这4个评估指标方面均有提升,其中MBE至少提升了43.3%。展开更多
针对自适应中值滤波在窗口迭代过程中存在像素点重复参与运算导致算法复杂度较高的问题,提出了一种改进的中值滤波算法.首先依据有效像素点与窗口中心点间的坐标距离来快速确定最佳滤波窗口尺寸,避免了窗口迭代造成的像素点重复排序;之...针对自适应中值滤波在窗口迭代过程中存在像素点重复参与运算导致算法复杂度较高的问题,提出了一种改进的中值滤波算法.首先依据有效像素点与窗口中心点间的坐标距离来快速确定最佳滤波窗口尺寸,避免了窗口迭代造成的像素点重复排序;之后对窗口内的有效像素点进行取中值操作,有效削弱了噪声点的干扰,进一步提升了图像滤波的质量.经实验验证,与自适应中值滤波算法比较,复杂度显著降低,峰值信噪比(peak signal to noise ratio,PSNR)值平均提高10 d B左右.和同类文献比较在算法复杂度和图像降噪效果间做出了一个较佳的权衡.最后将该算法应用于Kinect深度图降噪上获得了不错的效果.展开更多
基金the Program of “Study on Optimization and Supply-side Reliability of Oil Product Supply Chain Logistics System” funded under the National Natural Science Foundation of China, Grant Number 51874325
文摘The petrol truck routing problem is an important part of the petrol supply chain.This study focuses on determining routes for distributing petrol products from a depot to petrol stations with the objective of minimizing the total travel cost and the fixed cost required to use the trucks.We propose a mathematical model that considers petrol trucks returning to a depot multiple times and develop a heuristic algorithm based on a local branch-and-bound search with a tabu list and the Metropolis acceptance criterion.In addition,an approach that accelerates the solution process by adding several valid inequalities is presented.In this study,the trucks are homogeneous and have two compartments,and each truck can execute at most three tasks daily.The sales company arranges the transfer amount and the time windows for each station.The performance of the proposed algorithm is evaluated by comparing its results with the optimal results.In addition,a real-world case of routing petrol trucks in Beijing is studied to demonstrate the effectiveness of the proposed approach.
文摘高斯过程回归(Gaussian process regression,GPR)是一种基于高斯过程的非参数化贝叶斯回归方法,其可以灵活适应不同类型数据,用于建模和预测数据之间的复杂关系,具有拟合能力强、泛化能力好等特点。针对海量用户场景下用户量实时预测问题,提出一种基于GPR的用户量预测优化方法。在滑动窗口方法处理数据的基础上,选择合适的核函数,基于k折交叉验证得到最佳超参数组合以实现GPR模型训练,完成在线用户量的实时预测并进行性能评估。实验结果表明,相比于采用训练集中输出数据方差的50%作为信号噪声估计量的传统方案,所提方法具有较高的预测准确度,并且在测试集均方根误差(root mean square,RMS)、平均绝对误差(mean absolute error,MAE)、平均偏差(mean bias error,MBE)和决定系数R 2这4个评估指标方面均有提升,其中MBE至少提升了43.3%。
文摘针对自适应中值滤波在窗口迭代过程中存在像素点重复参与运算导致算法复杂度较高的问题,提出了一种改进的中值滤波算法.首先依据有效像素点与窗口中心点间的坐标距离来快速确定最佳滤波窗口尺寸,避免了窗口迭代造成的像素点重复排序;之后对窗口内的有效像素点进行取中值操作,有效削弱了噪声点的干扰,进一步提升了图像滤波的质量.经实验验证,与自适应中值滤波算法比较,复杂度显著降低,峰值信噪比(peak signal to noise ratio,PSNR)值平均提高10 d B左右.和同类文献比较在算法复杂度和图像降噪效果间做出了一个较佳的权衡.最后将该算法应用于Kinect深度图降噪上获得了不错的效果.
