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排序方式: 共有3159条查询结果,搜索用时 31 毫秒
1.
Solving large scale linear systems efficiently plays an important role in a petroleum reservoir simulator, and the key part is how to choose an effective parallel preconditioner. Properly choosing a good preconditioner has been beyond the pure algebraic field. An integrated preconditioner should include such components as physical background, characteristics of PDE mathematical model, nonlinear solving method, linear 相似文献
2.
在清华大学物理系成立60周年之际,我们对近年来清华大学物理系量子信息研究的主要进展情况作一介绍,包括量子搜索算法研究,核磁共振量子计算的实验研究,量子通讯的理论与实验研究.在量子搜索算法研究方面,我们提出了量子搜索算法的相位匹配,纠正了当时的一种错误观点,并且提出了一种成功率为100%的量子搜索算法,改进了Grover算法;在核磁共振量子计算实验方面,我们实现了2到7个量子比特的多种量子算法的实验演示;在量子通讯方面,我们提出了分布式传输的量子通讯的思想,应用于量子密钥分配、量子秘密共享、量子直接安全通讯等方面,构造了多个量子通讯的理论方案.在实验室,我们实现了2米距离的空间量子密码通讯的演示实验. 相似文献
3.
Mixed integer programming (MIP) models are extensively usedto aid strategic and tactical decision making in many businesssectors. Solving MIP models is a computationally intensive processand there is a need to develop solution approaches that enablelarger models to be solved within acceptable timeframes. Inthis paper, we describe the implementation of a two-stage parallelbranch and bound (PB & B) algorithm for MIP. In stage 1of the algorithm, a multiple heuristic search is implementedin which a number of alternative search trees are investigatedusing a forest search in the hope of finding a good solutionquickly. In stage 2, the search is reorganized so that the branchesof a chosen tree are investigated in parallel. A new heuristicis introduced, based on a best projection criterion, which evaluatesalternative B & B trees in order to choose one for investigationin stage 2 of the algorithm. The heuristic also serves as away of implementing a quality load balancing scheme for stage2 of the algorithm. The results of experimental investigationsare reported for a range of models taken from the MIPLIB libraryof benchmark problems. 相似文献
4.
Hossam A. Zaki 《Computational Optimization and Applications》1995,4(1):23-45
State-of-the-art computational results have shown that the shortest augmenting path (SAP) methods are more efficient than other primal-dual and primal-simplex based methods for solving the linear assignment problem on uniprocessor computers. There is, however, some controversy concerning their merits when compared with Bertsekas' auction algorithm on multiprocessor computers. In this study we investigate the performance of these competing methods on the Alliant FX/8. For each method, theoretical motivation, sources of parallelism and computational results are presented. 相似文献
5.
Madhu V. Nayakkankuppam 《Mathematical Programming》2007,109(2-3):477-504
We describe an approach to the parallel and distributed solution of large-scale, block structured semidefinite programs using
the spectral bundle method. Various elements of this approach (such as data distribution, an implicitly restarted Lanczos
method tailored to handle block diagonal structure, a mixed polyhedral-semidefinite subdifferential model, and other aspects
related to parallelism) are combined in an implementation called LAMBDA, which delivers faster solution times than previously
possible, and acceptable parallel scalability on sufficiently large problems.
This work was supported in part by NSF grants DMS-0215373 and DMS-0238008. 相似文献
7.
Ronald H. Nickel Igor Mikolic-Torreira Jon W. Tolle 《Computational Optimization and Applications》2006,35(1):109-126
Deployed US Navy aircraft carriers must stock a large number of spare parts to support the various types of aircraft embarked
on the ship. The sparing policy determines the spares that will be stocked on the ship to keep the embarked aircraft ready
to fly. Given a fleet of ten or more aircraft carriers and a cost of approximately 50 million dollars per carrier plus the
cost of spares maintained in warehouses in the United States, the sparing problem constitutes a significant portion of the
Navy’s resources. The objective of this work is to find a minimum-cost sparing policy that meets the readiness requirements
of the embarked aircraft. This is a very large, nonlinear, integer optimization problem. The cost function is piecewise linear
and convex while the constraint mapping is highly nonlinear. The distinguishing characteristics of this problem from an optimization
viewpoint are that a large number of decision variables are required to be integer and that the nonlinear constraint functions
are essentially “black box” functions; that is, they are very difficult (and expensive) to evaluate and their derivatives
are not available. Moreover, they are not convex. Integer programming problems with a large number of variables are difficult
to solve in general and most successful approaches to solving nonlinear integer problems have involved linear approximation
and relaxation techniques that, because of the complexity of the constraint functions, are inappropriate for attacking this
problem. We instead employ a pattern search method to each iteration of an interior point-type algorithm to solve the relaxed
version of the problem. From the solution found by the pattern search on each interior point iteration, we begin another pattern
search on the integer lattice to find a good integer solution. The best integer solution found across all interations is returned
as the optimal solution. The pattern searches are distributed across a local area network of non-dedicated, heterogeneous
computers in an office environment, thus, drastically reducing the time required to find the solution. 相似文献
8.
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10.
ResearchonDNAcomputingwasinitializedin1994 ,whenAdleman[1] proposedamethodofsolvingasmallinstanceoftheHamiltonianPathproblembyalaboratoryexperimentinvolvingDNAmolecules .Later,Lipton[2 ] demonstratedhowalargeclassofNP completeproblemscouldbesolvedbyencodingtheprobleminDNAmolecules .Inparticular ,LiptonshowedonefamousNP problem ,theso called“satisfiability”problem (SAT)andsubsequentlytheotherNP problemscouldbeencodedandsolvedusingmolecules .TheadvantagesofDNAcomputingareitsmassivepa… 相似文献