In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. ...Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.展开更多
A methodology for topology optimization based on element independent nodal density(EIND) is developed.Nodal densities are implemented as the design variables and interpolated onto element space to determine the densit...A methodology for topology optimization based on element independent nodal density(EIND) is developed.Nodal densities are implemented as the design variables and interpolated onto element space to determine the density of any point with Shepard interpolation function.The influence of the diameter of interpolation is discussed which shows good robustness.The new approach is demonstrated on the minimum volume problem subjected to a displacement constraint.The rational approximation for material properties(RAMP) method and a dual programming optimization algorithm are used to penalize the intermediate density point to achieve nearly 0-1 solutions.Solutions are shown to meet stability,mesh dependence or non-checkerboard patterns of topology optimization without additional constraints.Finally,the computational efficiency is greatly improved by multithread parallel computing with OpenMP.展开更多
A projected skill is adopted by use of the differential evolution (DE) algorithm to calculate a conditional nonlinear optimal perturbation (CNOP). The CNOP is the maximal value of a constrained optimization problem wi...A projected skill is adopted by use of the differential evolution (DE) algorithm to calculate a conditional nonlinear optimal perturbation (CNOP). The CNOP is the maximal value of a constrained optimization problem with a constraint condition, such as a ball constraint. The success of the DE algorithm lies in its ability to handle a non-differentiable and nonlinear cost function. In this study, the DE algorithm and the traditional optimization algorithms used to obtain the CNOPs are compared by analyzing a theoretical grassland ecosystem model and a dynamic global vegetation model. This study shows that the CNOPs generated by the DE algorithm are similar to those by the sequential quadratic programming (SQP) algorithm and the spectral projected gradients (SPG2) algorithm. If the cost function is non-differentiable, the CNOPs could also be caught with the DE algorithm. The numerical results suggest the DE algorithm can be employed to calculate the CNOP, especially when the cost function is non-differentiable.展开更多
Super-Resolution (SR) technique means to reconstruct High-Resolution (HR) images from a sequence of Low-Resolution (LR) observations,which has been a great focus for compressed video. Based on the theory of Projection...Super-Resolution (SR) technique means to reconstruct High-Resolution (HR) images from a sequence of Low-Resolution (LR) observations,which has been a great focus for compressed video. Based on the theory of Projection Onto Convex Set (POCS),this paper constructs Quantization Constraint Set (QCS) using the quantization information extracted from the video bit stream. By combining the statistical properties of image and the Human Visual System (HVS),a novel Adaptive Quantization Constraint Set (AQCS) is proposed. Simulation results show that AQCS-based SR al-gorithm converges at a fast rate and obtains better performance in both objective and subjective quality,which is applicable for compressed video.展开更多
In this paper a hybrid algorithm which combines the pattern search method and the genetic algorithm for unconstrained optimization is presented. The algorithm is a deterministic pattern search algorithm,but in the sea...In this paper a hybrid algorithm which combines the pattern search method and the genetic algorithm for unconstrained optimization is presented. The algorithm is a deterministic pattern search algorithm,but in the search step of pattern search algorithm,the trial points are produced by a way like the genetic algorithm. At each iterate, by reduplication,crossover and mutation, a finite set of points can be used. In theory,the algorithm is globally convergent. The most stir is the numerical results showing that it can find the global minimizer for some problems ,which other pattern search algorithms don＇t bear.展开更多
High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system suc...High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system such as complicated calibration process,cumbersome aided-instruments,strict limitation of working distance, this paper carries out an optical method in which two high-speed cameras with variable-zoom lenses are adopted as binocular stereo sensors of measurement system and a high-ac-curacy 3D target with fast reconstruction is designed. The intrinsic parameters of the sensors and the relative positions between coordinate systems are solved by the method of colinearity constrained optimization algorithm. The calibration process is easy to operate and the device is also of portability. Most importantly, the severe working distance limitation between sensors and measured body is solved, enhancing the adaptability of measurement system to environment. Experimental results show that when the sensors are in the range of 8 -16 m away from the measured body, system accuracy can reach up to ±0. 5 mm, which meets the requirements to measure the dynamic envelope curve of high-speed vehicle.展开更多
Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy co...Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform.The experimental results validate the effectiveness of the energy optimization methods.67.12% and 70.95% energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55%?8.80% performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67% of the results obtained by simulation.展开更多
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金Supported by the National 863 Project (No. 2003AA412010) and the National 973 Program of China (No. 2002CB312201)
文摘Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimiza- tion problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) algorithm is developed for nonlinear optimization problems with both contin- uous and discrete variables. In order to obtain a global optimum solution quickly, PSO algorithm is applied to solve the problem of blending scheduling under uncertainty. The calculation results based on an example of gasoline blending agree satisfactory with the ideal values, which illustrates that the PSO algorithm is valid and effective in solving the blending scheduling problem.
基金Projects(11372055,11302033)supported by the National Natural Science Foundation of ChinaProject supported by the Huxiang Scholar Foundation from Changsha University of Science and Technology,ChinaProject(2012KFJJ02)supported by the Key Labortory of Lightweight and Reliability Technology for Engineering Velicle,Education Department of Hunan Province,China
文摘A methodology for topology optimization based on element independent nodal density(EIND) is developed.Nodal densities are implemented as the design variables and interpolated onto element space to determine the density of any point with Shepard interpolation function.The influence of the diameter of interpolation is discussed which shows good robustness.The new approach is demonstrated on the minimum volume problem subjected to a displacement constraint.The rational approximation for material properties(RAMP) method and a dual programming optimization algorithm are used to penalize the intermediate density point to achieve nearly 0-1 solutions.Solutions are shown to meet stability,mesh dependence or non-checkerboard patterns of topology optimization without additional constraints.Finally,the computational efficiency is greatly improved by multithread parallel computing with OpenMP.
基金provided by grants from the National Basic Research Program of China (Grant No. 2006CB400503)LASG Free Exploration Fund+1 种基金LASG State Key Laboratory Special Fundthe KZCX3-SW-230 of the Chinese Academy of Sciences
文摘A projected skill is adopted by use of the differential evolution (DE) algorithm to calculate a conditional nonlinear optimal perturbation (CNOP). The CNOP is the maximal value of a constrained optimization problem with a constraint condition, such as a ball constraint. The success of the DE algorithm lies in its ability to handle a non-differentiable and nonlinear cost function. In this study, the DE algorithm and the traditional optimization algorithms used to obtain the CNOPs are compared by analyzing a theoretical grassland ecosystem model and a dynamic global vegetation model. This study shows that the CNOPs generated by the DE algorithm are similar to those by the sequential quadratic programming (SQP) algorithm and the spectral projected gradients (SPG2) algorithm. If the cost function is non-differentiable, the CNOPs could also be caught with the DE algorithm. The numerical results suggest the DE algorithm can be employed to calculate the CNOP, especially when the cost function is non-differentiable.
基金the Natural Science Foundation of Jiangsu Province (No.BK2004151).
文摘Super-Resolution (SR) technique means to reconstruct High-Resolution (HR) images from a sequence of Low-Resolution (LR) observations,which has been a great focus for compressed video. Based on the theory of Projection Onto Convex Set (POCS),this paper constructs Quantization Constraint Set (QCS) using the quantization information extracted from the video bit stream. By combining the statistical properties of image and the Human Visual System (HVS),a novel Adaptive Quantization Constraint Set (AQCS) is proposed. Simulation results show that AQCS-based SR al-gorithm converges at a fast rate and obtains better performance in both objective and subjective quality,which is applicable for compressed video.
文摘In this paper a hybrid algorithm which combines the pattern search method and the genetic algorithm for unconstrained optimization is presented. The algorithm is a deterministic pattern search algorithm,but in the search step of pattern search algorithm,the trial points are produced by a way like the genetic algorithm. At each iterate, by reduplication,crossover and mutation, a finite set of points can be used. In theory,the algorithm is globally convergent. The most stir is the numerical results showing that it can find the global minimizer for some problems ,which other pattern search algorithms don＇t bear.
基金National Science and Technology Major Project(No.2016ZX04003001)
文摘High-speed vehicle dynamic envelope curve is defined as the maximum limit outline affected by a variety of adverse factors while the train is running. Considering the difficulties in the current measurement system such as complicated calibration process,cumbersome aided-instruments,strict limitation of working distance, this paper carries out an optical method in which two high-speed cameras with variable-zoom lenses are adopted as binocular stereo sensors of measurement system and a high-ac-curacy 3D target with fast reconstruction is designed. The intrinsic parameters of the sensors and the relative positions between coordinate systems are solved by the method of colinearity constrained optimization algorithm. The calibration process is easy to operate and the device is also of portability. Most importantly, the severe working distance limitation between sensors and measured body is solved, enhancing the adaptability of measurement system to environment. Experimental results show that when the sensors are in the range of 8 -16 m away from the measured body, system accuracy can reach up to ±0. 5 mm, which meets the requirements to measure the dynamic envelope curve of high-speed vehicle.
基金Projects(60903044,61170049) supported by National Natural Science Foundation of China
文摘Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform.The experimental results validate the effectiveness of the energy optimization methods.67.12% and 70.95% energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55%?8.80% performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67% of the results obtained by simulation.
