Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the in...Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the interval numbers at the same time. It also gives the optimization method of weights in the grey target. We get the optimum coordinated vector utilizing the combination assigning method, based on the local optimization of various schemes. So it can shift the weights of interval number into real number form and sequence it according to the weighted off-target distance. Finally the effectiveness and practicality of the model is proved by a real project.展开更多
A novel method based on ant colony optimization (ACO), algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from th...A novel method based on ant colony optimization (ACO), algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.展开更多
In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase de...In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase decision algorithm of replica allocation is proposed. The algorithm which makes use of auto-regression model dynamically predicts the future count of READ and WRITE operation, and then determines location and redundancy of replicas by considering availability, CPU and bands of the network. The algorithm can not only ensure the requirement of availability, but also reduce the system resources consumed by all the operations in a great scale. Analysis and test show that communication complexity and time complexity of the algorithm satisfy O(n), resource optimizing scale increases with the increase of READ count.展开更多
城市综合能源系统(urban integrated energy system,UIES)作为城市能源生产、运输、消费的载体,其运行中需要具备充足的灵活性来应对各种不确定波动。从灵活性的定义出发,该文提出基于不确定量波动范围的灵活性调度指标。为降低传统区...城市综合能源系统(urban integrated energy system,UIES)作为城市能源生产、运输、消费的载体,其运行中需要具备充足的灵活性来应对各种不确定波动。从灵活性的定义出发,该文提出基于不确定量波动范围的灵活性调度指标。为降低传统区间数在描述不确定量时由于概率信息丢失而导致的决策保守性,提出采用考虑相关性的多带区间数(multi-band interval number,MBIN)描述不确定量的方法,并通过历史数据和插值法得到连续的累积分布函数。提出以运行成本最小和可容纳室外温度和光照强度不确定波动范围最大的UIES多目标区间优化调度模型。采用区间可能度方法处理含有传统区间数和考虑相关性的MBIN的约束条件,将原问题转化为确定性多目标混合整数线性规划问题。通过一种直接求解多目标优化问题折中最优解的方法,将此问题进一步转化为可以高效求得折中最优解的单目标混合整数线性规划问题。最后,通过一个含有农业-工业-商业园区的实际UIES的算例分析,结果验证所提出模型和求解方法的正确有效性。展开更多
最优线程数设置是影响多线程程序性能和功耗的关键之一。然而,目前寻找最优线程数的算法通常是从单一固定起点开始搜索,往往会造成搜索精度低、搜索开销大的问题。最优线程数的分布和位置与多种因素有关,包括程序所属类型、优化目标(性...最优线程数设置是影响多线程程序性能和功耗的关键之一。然而,目前寻找最优线程数的算法通常是从单一固定起点开始搜索,往往会造成搜索精度低、搜索开销大的问题。最优线程数的分布和位置与多种因素有关,包括程序所属类型、优化目标(性能、功耗和EDP(Energy-delay Product))、并行的多线程区域、软硬件配置参数等。围绕能效优先的最优线程数搜索问题,提出了能效优先的特定起点分类最优线程数搜索算法(Energy-Efficiency-First Optimal Thread Number Search Algorithm based on Specific Starting Point Classification,简称TS^(3)方法)”,通过设计基于程序分类的特殊起点设定方法来确定搜索起点,并采用启发式算法和二分查找方法搜索最优线程数,提升搜索效率,有效提升了能效优先目标(性能最优、功耗最优、能效EDP最优)下的最优线程数搜索精度并降低了搜索开销。在两个x86和一个ARM平台上用8个benchmark对算法有效性进行了详细实验验证,结果表明,与Baseline相比,TS^(3)方法的性能平均提升0.29%(平台A)、0.17%(平台B)、10.77%(平台C);功耗平均降低2.35%(平台A)、1.87%(平台B)、15.97%(平台C);EDP平均降低6.36%(平台A)、5.07%(平台B)、46.94%(平台C)。在3个平台上,与目前经典搜索方法相比,TS^(3)方法的性能平均提升10.16%,功耗平均降低13.45%,EDP平均降低23.77%;搜索开销平均降低86.8%。展开更多
基金supported by the National Natural Science Foundation for Young Scholar of China(70901040)the Doctoral Fund of Ministry of Education of China(200802870020)the Nanjing University of Aeronautics and Astronautics Innovation Foundation(Y0811-091).
文摘Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the interval numbers at the same time. It also gives the optimization method of weights in the grey target. We get the optimum coordinated vector utilizing the combination assigning method, based on the local optimization of various schemes. So it can shift the weights of interval number into real number form and sequence it according to the weighted off-target distance. Finally the effectiveness and practicality of the model is proved by a real project.
文摘A novel method based on ant colony optimization (ACO), algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.
文摘In distributed parallel server system, location and redundancy of repficas have great influence on availability and efficiency of the system. In order to improve availability and efficiency of the system, two phase decision algorithm of replica allocation is proposed. The algorithm which makes use of auto-regression model dynamically predicts the future count of READ and WRITE operation, and then determines location and redundancy of replicas by considering availability, CPU and bands of the network. The algorithm can not only ensure the requirement of availability, but also reduce the system resources consumed by all the operations in a great scale. Analysis and test show that communication complexity and time complexity of the algorithm satisfy O(n), resource optimizing scale increases with the increase of READ count.
文摘最优线程数设置是影响多线程程序性能和功耗的关键之一。然而,目前寻找最优线程数的算法通常是从单一固定起点开始搜索,往往会造成搜索精度低、搜索开销大的问题。最优线程数的分布和位置与多种因素有关,包括程序所属类型、优化目标(性能、功耗和EDP(Energy-delay Product))、并行的多线程区域、软硬件配置参数等。围绕能效优先的最优线程数搜索问题,提出了能效优先的特定起点分类最优线程数搜索算法(Energy-Efficiency-First Optimal Thread Number Search Algorithm based on Specific Starting Point Classification,简称TS^(3)方法)”,通过设计基于程序分类的特殊起点设定方法来确定搜索起点,并采用启发式算法和二分查找方法搜索最优线程数,提升搜索效率,有效提升了能效优先目标(性能最优、功耗最优、能效EDP最优)下的最优线程数搜索精度并降低了搜索开销。在两个x86和一个ARM平台上用8个benchmark对算法有效性进行了详细实验验证,结果表明,与Baseline相比,TS^(3)方法的性能平均提升0.29%(平台A)、0.17%(平台B)、10.77%(平台C);功耗平均降低2.35%(平台A)、1.87%(平台B)、15.97%(平台C);EDP平均降低6.36%(平台A)、5.07%(平台B)、46.94%(平台C)。在3个平台上,与目前经典搜索方法相比,TS^(3)方法的性能平均提升10.16%,功耗平均降低13.45%,EDP平均降低23.77%;搜索开销平均降低86.8%。