In this paper, a new trust region algorithm for unconstrained LC1 optimization problems is given. Compare with those existing trust regiion methods, this algorithm has a different feature: it obtains a stepsize at eac...In this paper, a new trust region algorithm for unconstrained LC1 optimization problems is given. Compare with those existing trust regiion methods, this algorithm has a different feature: it obtains a stepsize at each iteration not by soloving a quadratic subproblem with a trust region bound, but by solving a system of linear equations. Thus it reduces computational complexity and improves computation efficiency. It is proven that this algorithm is globally convergent and locally superlinear under some conditions.展开更多
In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best ite...In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best iterative point being on the boundary. By doing these, the trust region subproblems are constructed at a new way different with the traditional ones. Then, we test the efficiency of the new line search and trust region algorithm on some standard benchmarking. The computational results reveal that, for most test problems, the number of function and gradient calculations are reduced significantly.展开更多
A trust region algorithm for equality constrained optimization is given in this paper.The algorithm does not enforce strict monotonicity of the merit function for every iteration.Global convergence of the algorithm i...A trust region algorithm for equality constrained optimization is given in this paper.The algorithm does not enforce strict monotonicity of the merit function for every iteration.Global convergence of the algorithm is proved under the same conditions of usual trust region method.展开更多
In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorith...In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.展开更多
The film-covered sweet potato transplanting method requires ensuring the transplantation conditions of small planting holes and large lateral displacement.In the soil insertion phase,the transplantation machine requir...The film-covered sweet potato transplanting method requires ensuring the transplantation conditions of small planting holes and large lateral displacement.In the soil insertion phase,the transplantation machine requires a mechanism design with multiple timed poses,and the existing design methods are still imperfect.For this reason,this article proposes a multi-target trust region parameter-guided optimization algorithm.This algorithm aims to achieve multi-objective optimization design with more timed pose conditions starting from individual timed pose conditions.First,multi-target problems are decomposed into multiple subproblems,and the parameter arrays are kept with the minimum polymerization value of each subproblem.Then,the approximate function value reduction for each target is calculated using this parameter set,and the step size for the next iteration of each subproblem is determined by comparing this approximate reduction with the actual reduction.After many iteration calculations,the parameter arrays end the calculation when the parameter group is no longer updated.This paper uses the design of a film-covered sweet potato transplanting mechanism as a complex optimized application example.The algorithm is used to obtain the optimization results of the target values of eight groups of institutions.The smallest hole is 2.99 mm,and the horizontal transplanting distance is 108.40 mm.The maximum hole is 17.64 mm,and the horizontal transplanting distance is 124.97 mm.Considering the size of the hole and the horizontal transplanting distance of sweet potato transplanting,the mechanism’s target value of the horizontal transplanting distance at 119.92 mm and the hole size at 0.31 mm were selected to design the sweet potato transplanting machine.The correctness of the results is verified,which reflects the practicability of the algorithm.展开更多
To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, an improved artificial potential field model （IAPFM） was established, then a new path planning method ...To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, an improved artificial potential field model （IAPFM） was established, then a new path planning method combining the IAPFM with optimization algorithm （trust region algorithm） is proposed. Attractive force between the robot and the target location, and repulsive force between the robot and the obstacles are both converted to the potential field intensity; and filled potential field is used to guide the robot to go out of the local minimum points ; on this basis, the effect of dynamic obstacles velocity and the robot＇s velocity is consid thers and the IAPFM is established, then both the expressions of the attractive potential field and the repulsive potential field are obtained. The trust region algorithm is used to search the minimum value of the sum of all the potential field inten- sities within the movement scope which the robot can arrive in a sampling period. Connecting of all the points which hare the minimum intensity in every sampling period constitutes the global optimization path. Experiment result shows that the method can meet the real-time requirement, and is able to execute the mobile robot path planning task effectively in the dynamic environment.展开更多
A trust region algorithm for equality constrained optimization is proposed, which is a nonmonotone one in a certain sense. The augmented Lagrangian function is used as a merit function. Under certain conditions, the g...A trust region algorithm for equality constrained optimization is proposed, which is a nonmonotone one in a certain sense. The augmented Lagrangian function is used as a merit function. Under certain conditions, the global convergence theorems of the algorithm are proved.展开更多
The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (L...The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter a. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious finding the regularization parameters and truncation levels. Some numerical tests on remotely sensed images are given to show that the trust region method is promising.展开更多
A class of nonmonotone trust region algorithms is presented for unconstrained optimizations. Under suitable conditions, the global and Q quadratic convergences of the algorithm are proved. Several rules of choosing tr...A class of nonmonotone trust region algorithms is presented for unconstrained optimizations. Under suitable conditions, the global and Q quadratic convergences of the algorithm are proved. Several rules of choosing trial steps and trust region radii are also discussed.展开更多
In this paper we present a nonmonotone trust region algorithm for general nonlinear constrained optimization problems. The main idea of this paper is to combine Yuan's technique[1] with a nonmonotone method simila...In this paper we present a nonmonotone trust region algorithm for general nonlinear constrained optimization problems. The main idea of this paper is to combine Yuan's technique[1] with a nonmonotone method similar to Ke and Han [2]. This new algorithm may not only keep the robust properties of the algorithm given by Yuan, but also have some advantages led by the nonmonotone technique. Under very mild conditions, global convergence for the algorithm is given. Numerical experiments demonstrate the efficiency of the algorithm.展开更多
为求解黎曼流形上的大规模可分离问题,Kasai等人在(Advances of the neural information processing systems, 31, 2018)中提出了使用非精确梯度和非精确Hessian的黎曼信赖域算法,并给出了该算法的迭代复杂度(只有证明思路,没有具体证明...为求解黎曼流形上的大规模可分离问题,Kasai等人在(Advances of the neural information processing systems, 31, 2018)中提出了使用非精确梯度和非精确Hessian的黎曼信赖域算法,并给出了该算法的迭代复杂度(只有证明思路,没有具体证明)。我们指出在该文献的假设条件下,按照其思路不能证明出相应的结果。本文提出了不同的参数假设,并证明了算法具有类似的迭代复杂度。展开更多
文摘In this paper, a new trust region algorithm for unconstrained LC1 optimization problems is given. Compare with those existing trust regiion methods, this algorithm has a different feature: it obtains a stepsize at each iteration not by soloving a quadratic subproblem with a trust region bound, but by solving a system of linear equations. Thus it reduces computational complexity and improves computation efficiency. It is proven that this algorithm is globally convergent and locally superlinear under some conditions.
文摘In this paper, we present a new line search and trust region algorithm for unconstrained optimization problems. The trust region center locates at somewhere in the negative gradient direction with the current best iterative point being on the boundary. By doing these, the trust region subproblems are constructed at a new way different with the traditional ones. Then, we test the efficiency of the new line search and trust region algorithm on some standard benchmarking. The computational results reveal that, for most test problems, the number of function and gradient calculations are reduced significantly.
文摘A trust region algorithm for equality constrained optimization is given in this paper.The algorithm does not enforce strict monotonicity of the merit function for every iteration.Global convergence of the algorithm is proved under the same conditions of usual trust region method.
基金Supported by CERG: CityU 101005 of the Government of Hong Kong SAR, Chinathe National Natural ScienceFoundation of China, the Specialized Research Fund of Doctoral Program of Higher Education of China (Grant No.20040319003)the Natural Science Fund of Jiangsu Province of China (Grant No. BK2006214)
文摘In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative. We establish the global convergence of the algorithm under reasonable assumptions.
基金supported by the Key Research Projects of China(Grant No.2022YFD2001800)the National Natural Science Foundation of China(Grant No.32071909)Zhejiang Provincial Natural Science Foundation(Grant No.LD24E05007).
文摘The film-covered sweet potato transplanting method requires ensuring the transplantation conditions of small planting holes and large lateral displacement.In the soil insertion phase,the transplantation machine requires a mechanism design with multiple timed poses,and the existing design methods are still imperfect.For this reason,this article proposes a multi-target trust region parameter-guided optimization algorithm.This algorithm aims to achieve multi-objective optimization design with more timed pose conditions starting from individual timed pose conditions.First,multi-target problems are decomposed into multiple subproblems,and the parameter arrays are kept with the minimum polymerization value of each subproblem.Then,the approximate function value reduction for each target is calculated using this parameter set,and the step size for the next iteration of each subproblem is determined by comparing this approximate reduction with the actual reduction.After many iteration calculations,the parameter arrays end the calculation when the parameter group is no longer updated.This paper uses the design of a film-covered sweet potato transplanting mechanism as a complex optimized application example.The algorithm is used to obtain the optimization results of the target values of eight groups of institutions.The smallest hole is 2.99 mm,and the horizontal transplanting distance is 108.40 mm.The maximum hole is 17.64 mm,and the horizontal transplanting distance is 124.97 mm.Considering the size of the hole and the horizontal transplanting distance of sweet potato transplanting,the mechanism’s target value of the horizontal transplanting distance at 119.92 mm and the hole size at 0.31 mm were selected to design the sweet potato transplanting machine.The correctness of the results is verified,which reflects the practicability of the algorithm.
基金Supported by the National High Technology Research and Development Programme of China（ No. 2006AA04Z245 ） and China Postdoctoral Science Foundation （ No. 200904500988 ）.
文摘To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning, an improved artificial potential field model （IAPFM） was established, then a new path planning method combining the IAPFM with optimization algorithm （trust region algorithm） is proposed. Attractive force between the robot and the target location, and repulsive force between the robot and the obstacles are both converted to the potential field intensity; and filled potential field is used to guide the robot to go out of the local minimum points ; on this basis, the effect of dynamic obstacles velocity and the robot＇s velocity is consid thers and the IAPFM is established, then both the expressions of the attractive potential field and the repulsive potential field are obtained. The trust region algorithm is used to search the minimum value of the sum of all the potential field inten- sities within the movement scope which the robot can arrive in a sampling period. Connecting of all the points which hare the minimum intensity in every sampling period constitutes the global optimization path. Experiment result shows that the method can meet the real-time requirement, and is able to execute the mobile robot path planning task effectively in the dynamic environment.
基金Project supported by the National Natural Science Foundation of China and Postdoctoral Foundation of China.
文摘A trust region algorithm for equality constrained optimization is proposed, which is a nonmonotone one in a certain sense. The augmented Lagrangian function is used as a merit function. Under certain conditions, the global convergence theorems of the algorithm are proved.
基金supported by the National Natural Science Foundation of China(Grant Nos.19731010 and 10231060)the Knowledge Innovation Program of CAS+1 种基金was supported by SRF for ROSS,SEM partially supported by the Special Innovation Fund for graduate students of CAS.
文摘The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter a. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious finding the regularization parameters and truncation levels. Some numerical tests on remotely sensed images are given to show that the trust region method is promising.
文摘A class of nonmonotone trust region algorithms is presented for unconstrained optimizations. Under suitable conditions, the global and Q quadratic convergences of the algorithm are proved. Several rules of choosing trial steps and trust region radii are also discussed.
基金This work was done when the author was studying in the State Key Laboratory of Scientific and Engi- neering Computing, Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of Sciences, P. O. Box 2719, Beijing 10008
文摘In this paper we present a nonmonotone trust region algorithm for general nonlinear constrained optimization problems. The main idea of this paper is to combine Yuan's technique[1] with a nonmonotone method similar to Ke and Han [2]. This new algorithm may not only keep the robust properties of the algorithm given by Yuan, but also have some advantages led by the nonmonotone technique. Under very mild conditions, global convergence for the algorithm is given. Numerical experiments demonstrate the efficiency of the algorithm.
文摘为求解黎曼流形上的大规模可分离问题,Kasai等人在(Advances of the neural information processing systems, 31, 2018)中提出了使用非精确梯度和非精确Hessian的黎曼信赖域算法,并给出了该算法的迭代复杂度(只有证明思路,没有具体证明)。我们指出在该文献的假设条件下,按照其思路不能证明出相应的结果。本文提出了不同的参数假设,并证明了算法具有类似的迭代复杂度。
