In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transform...In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transformation to derive the search direction.It is shown that the proximity measure reduces quadratically at each iteration.Moreover,the iteration bound of the algorithm is as good as the best-known polynomial complexity for these types of problems.Furthermore,numerical results are presented to show the efficiency of the proposed algorithm.展开更多
In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear ...In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.展开更多
Cloud data centers consume a multitude of power leading to the problem of high energy consumption. In order to solve this problem, an energy-efficient virtual machine(VM) consolidation algorithm named PVDE(prediction-...Cloud data centers consume a multitude of power leading to the problem of high energy consumption. In order to solve this problem, an energy-efficient virtual machine(VM) consolidation algorithm named PVDE(prediction-based VM deployment algorithm for energy efficiency) is presented. The proposed algorithm uses linear weighted method to predict the load of a host and classifies the hosts in the data center, based on the predicted host load, into four classes for the purpose of VMs migration. We also propose four types of VM selection algorithms for the purpose of determining potential VMs to be migrated. We performed extensive performance analysis of the proposed algorithms. Experimental results show that, in contrast to other energy-saving algorithms, the algorithm proposed in this work significantly reduces the energy consumption and maintains low service level agreement(SLA) violations.展开更多
To obtain a good interference fringe contrast and high fidelity,an automated beam iterative alignment is achieved in scanning beam interference lithography(SBIL).To solve the problem of alignment failure caused by a l...To obtain a good interference fringe contrast and high fidelity,an automated beam iterative alignment is achieved in scanning beam interference lithography(SBIL).To solve the problem of alignment failure caused by a large beam angle(or position)overshoot exceeding the detector range while also speeding up the convergence,a weighted iterative algorithm using a weight parameter that is changed linearly piecewise is proposed.The changes in the beam angle and position deviation during the alignment process based on different iterative algorithms are compared by experiment and simulation.The results show that the proposed iterative algorithm can be used to suppress the beam angle(or position)overshoot,avoiding alignment failure caused by over-ranging.In addition,the convergence speed can be effectively increased.The algorithm proposed can optimize the beam alignment process in SBIL.展开更多
基金Supported by the Optimisation Theory and Algorithm Research Team(Grant No.23kytdzd004)University Science Research Project of Anhui Province(Grant No.2024AH050631)the General Programs for Young Teacher Cultivation of Educational Commission of Anhui Province(Grant No.YQYB2023090).
文摘In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transformation to derive the search direction.It is shown that the proximity measure reduces quadratically at each iteration.Moreover,the iteration bound of the algorithm is as good as the best-known polynomial complexity for these types of problems.Furthermore,numerical results are presented to show the efficiency of the proposed algorithm.
基金Supported by University Science Research Project of Anhui Province(2023AH052921)Outstanding Youth Talent Project of Anhui Province(gxyq2021254)。
文摘In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.
基金Projects(61572525,61272148)supported by the National Natural Science Foundation of ChinaProject(20120162110061)supported by the PhD Programs Foundation of Ministry of Education of China+1 种基金Project(CX2014B066)supported by the Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(2014zzts044)supported by the Fundamental Research Funds for the Central Universities,China
文摘Cloud data centers consume a multitude of power leading to the problem of high energy consumption. In order to solve this problem, an energy-efficient virtual machine(VM) consolidation algorithm named PVDE(prediction-based VM deployment algorithm for energy efficiency) is presented. The proposed algorithm uses linear weighted method to predict the load of a host and classifies the hosts in the data center, based on the predicted host load, into four classes for the purpose of VMs migration. We also propose four types of VM selection algorithms for the purpose of determining potential VMs to be migrated. We performed extensive performance analysis of the proposed algorithms. Experimental results show that, in contrast to other energy-saving algorithms, the algorithm proposed in this work significantly reduces the energy consumption and maintains low service level agreement(SLA) violations.
基金The research was supported by the National Natural Science Foundation of China(NSFC)(Grant No.61227901)Jilin Province Science&Technology Development Program Project in China(Grant No.20190103157JH).
文摘To obtain a good interference fringe contrast and high fidelity,an automated beam iterative alignment is achieved in scanning beam interference lithography(SBIL).To solve the problem of alignment failure caused by a large beam angle(or position)overshoot exceeding the detector range while also speeding up the convergence,a weighted iterative algorithm using a weight parameter that is changed linearly piecewise is proposed.The changes in the beam angle and position deviation during the alignment process based on different iterative algorithms are compared by experiment and simulation.The results show that the proposed iterative algorithm can be used to suppress the beam angle(or position)overshoot,avoiding alignment failure caused by over-ranging.In addition,the convergence speed can be effectively increased.The algorithm proposed can optimize the beam alignment process in SBIL.
