For the expected value formulation of stochastic linear complementarity problem, we establish modulus-based matrix splitting iteration methods. The convergence of the new methods is discussed when the coefficient matr...For the expected value formulation of stochastic linear complementarity problem, we establish modulus-based matrix splitting iteration methods. The convergence of the new methods is discussed when the coefficient matrix is a positive definite matrix or a positive semi-definite matrix, respectively. The advantages of the new methods are that they can solve the large scale stochastic linear complementarity problem, and spend less computational time. Numerical results show that the new methods are efficient and suitable for solving the large scale problems.展开更多
In this paper,by means of constructing the linear complementarity problems into the corresponding absolute value equation,we raise an iteration method,called as the nonlinear lopsided HSS-like modulus-based matrix spl...In this paper,by means of constructing the linear complementarity problems into the corresponding absolute value equation,we raise an iteration method,called as the nonlinear lopsided HSS-like modulus-based matrix splitting iteration method,for solving the linear complementarity problems whose coefficient matrix in R^(n×n)is large sparse and positive definite.From the convergence analysis,it is appreciable to see that the proposed method will converge to its accurate solution under appropriate conditions.Numerical examples demonstrate that the presented method precede to other methods in practical implementation.展开更多
In this paper,we present a modulus-based multisplitting iteration method based on multisplitting of the system matrix for a class of weakly nonlinear complementarity problem.And we prove the convergence of the method ...In this paper,we present a modulus-based multisplitting iteration method based on multisplitting of the system matrix for a class of weakly nonlinear complementarity problem.And we prove the convergence of the method when the system matrix is an H_(+)-matrix.Finally,we give two numerical examples.展开更多
In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent im...In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent implicit fixed-point equation, then introduces a smoothing function to obtain its approximation solutions. The convergence analysis of the algorithm was given, and the efficiency of the algorithms was verified by numerical experiments.展开更多
To reduce the communication among processors and improve the computing time for solving linear complementarity problems, we present a two-step modulus-based syn- chronous multisplitting iteration method and the corres...To reduce the communication among processors and improve the computing time for solving linear complementarity problems, we present a two-step modulus-based syn- chronous multisplitting iteration method and the corresponding symmetric modulus-based multisplitting relaxation methods. The convergence theorems are established when the system matrix is an H+-matrix, which improve the existing convergence theory. Numeri- cal results show that the symmetric modulus-based multisplitting relaxation methods are effective in actual implementation.展开更多
We propose the two-step modulus-based matrix splitting iteration methods for a class of nonlinear complementarity problems.The corresponding convergence the-ory is established when the system matrix is an H_(+)-matrix...We propose the two-step modulus-based matrix splitting iteration methods for a class of nonlinear complementarity problems.The corresponding convergence the-ory is established when the system matrix is an H_(+)-matrix.Theoretical analysis gives the choice of parameter matrix involved based on the H-compatible splitting of the sys-tem matrix.Moreover,in actual implementation,the choices of iterative parameters for two-step modulus-based accelerated overrelaxation methods are studied.Numeri-cal experiments show that the method is efficient and further verify the convergence theorems.展开更多
As applying the Levenberg-Marquardt method to the reformulation of linear complementarity problem,a modulus-based Levenberg-Marquardt method with non-monotone line search is established and the global convergence resu...As applying the Levenberg-Marquardt method to the reformulation of linear complementarity problem,a modulus-based Levenberg-Marquardt method with non-monotone line search is established and the global convergence result is presented.Numerical experiments show that the proposed method is efficient and outperforms the modulus-based matrix splitting iteration method.展开更多
Linear complementarity problems have drawn considerable attention in recent years due to their wide applications.In this article,we introduce the two-step two-sweep modulus-based matrix splitting(TSTM)iteration method...Linear complementarity problems have drawn considerable attention in recent years due to their wide applications.In this article,we introduce the two-step two-sweep modulus-based matrix splitting(TSTM)iteration method and two-sweep modulus-based matrix splitting type II(TM II)iteration method which are a combination of the two-step modulus-based method and the two-sweep modulus-based method,as two more effective ways to solve the linear complementarity problems.The convergence behavior of these methods is discussed when the system matrix is either a positive-definite or an H+-matrix.Finally,numerical experiments are given to show the efficiency of our proposed methods.展开更多
文摘For the expected value formulation of stochastic linear complementarity problem, we establish modulus-based matrix splitting iteration methods. The convergence of the new methods is discussed when the coefficient matrix is a positive definite matrix or a positive semi-definite matrix, respectively. The advantages of the new methods are that they can solve the large scale stochastic linear complementarity problem, and spend less computational time. Numerical results show that the new methods are efficient and suitable for solving the large scale problems.
基金This work is supported by the National Natural Science Foundation of China with No.11461046the Natural Science Foundation of Jiangxi Province of China with Nos.20181ACB20001 and 20161ACB21005.
文摘In this paper,by means of constructing the linear complementarity problems into the corresponding absolute value equation,we raise an iteration method,called as the nonlinear lopsided HSS-like modulus-based matrix splitting iteration method,for solving the linear complementarity problems whose coefficient matrix in R^(n×n)is large sparse and positive definite.From the convergence analysis,it is appreciable to see that the proposed method will converge to its accurate solution under appropriate conditions.Numerical examples demonstrate that the presented method precede to other methods in practical implementation.
基金This work was supported by the National Natural Science Foundation of China(Grant No.11771275)the Science and Technology Program of Shandong Universities(No.J16LI04).
文摘In this paper,we present a modulus-based multisplitting iteration method based on multisplitting of the system matrix for a class of weakly nonlinear complementarity problem.And we prove the convergence of the method when the system matrix is an H_(+)-matrix.Finally,we give two numerical examples.
文摘In this paper, a class of smoothing modulus-based iterative method was presented for solving implicit complementarity problems. The main idea was to transform the implicit complementarity problem into an equivalent implicit fixed-point equation, then introduces a smoothing function to obtain its approximation solutions. The convergence analysis of the algorithm was given, and the efficiency of the algorithms was verified by numerical experiments.
文摘To reduce the communication among processors and improve the computing time for solving linear complementarity problems, we present a two-step modulus-based syn- chronous multisplitting iteration method and the corresponding symmetric modulus-based multisplitting relaxation methods. The convergence theorems are established when the system matrix is an H+-matrix, which improve the existing convergence theory. Numeri- cal results show that the symmetric modulus-based multisplitting relaxation methods are effective in actual implementation.
基金This work was supported by the National Natural Science Foundation of China(No.11271289,11701221)the Fundamental Research Funds for the Central Universities.
文摘We propose the two-step modulus-based matrix splitting iteration methods for a class of nonlinear complementarity problems.The corresponding convergence the-ory is established when the system matrix is an H_(+)-matrix.Theoretical analysis gives the choice of parameter matrix involved based on the H-compatible splitting of the sys-tem matrix.Moreover,in actual implementation,the choices of iterative parameters for two-step modulus-based accelerated overrelaxation methods are studied.Numeri-cal experiments show that the method is efficient and further verify the convergence theorems.
基金This research is supported by National Science Foundation of China(41725017)National Basic Research Program of China under grant number 2014CB845906+1 种基金It is also partially supported by the CAS/CAFEA international partnership Program for creative research teams(No.KZZD-EW-TZ-19 and KZZD-EW-TZ-15)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB18010202)。
文摘As applying the Levenberg-Marquardt method to the reformulation of linear complementarity problem,a modulus-based Levenberg-Marquardt method with non-monotone line search is established and the global convergence result is presented.Numerical experiments show that the proposed method is efficient and outperforms the modulus-based matrix splitting iteration method.
文摘Linear complementarity problems have drawn considerable attention in recent years due to their wide applications.In this article,we introduce the two-step two-sweep modulus-based matrix splitting(TSTM)iteration method and two-sweep modulus-based matrix splitting type II(TM II)iteration method which are a combination of the two-step modulus-based method and the two-sweep modulus-based method,as two more effective ways to solve the linear complementarity problems.The convergence behavior of these methods is discussed when the system matrix is either a positive-definite or an H+-matrix.Finally,numerical experiments are given to show the efficiency of our proposed methods.