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1.
An Algorithm for Strictly Convex Quadratic Programming with Box Constraints   总被引:1,自引:0,他引:1  
1IntroductionWeconsiderastrictlyconvex(i.e.,positivedefinite)quadraticprogrammingproblemsubjecttoboxconstraints:t-iereA=[aij]isannxnsymmetricpositivedefinitematrix,andb,canddaren-vectors.Letg(x)bethegradient,Ax b,off(x)atx.Withoutlossofgeneralityweassumebothcianddiarefinitenumbers,ci相似文献   

2.
Using a few very basic observations, we proposed recently a direct and finite algorithm for the computation of the l regression line on a discrete set under the assumption that In this paper, we extend the algorithm to the case with at least one, possibly multiple y-values for each distinct x_i. Our algorithm finds all the regression lines in O(n 2) operations in the worst-case scenario and improves the existing best-known computational complexity result for this problem. Numerical results on random problems are included.  相似文献   

3.
In this paper, on the basis of the logarithmic barrier function and KKT conditions , we propose a combined homotopy infeasible interior-point method (CHIIP) for convex nonlinear programming problems. For any convex nonlinear programming, without strict convexity for the logarithmic barrier function, we get different solutions of the convex programming in different cases by CHIIP method.  相似文献   

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We prove the following generalization of the classical Shephard–Todd–Chevalley Theorem. Let G be a finite group of graded algebra automorphisms of a skew polynomial ring \(A:=k_{p_{ij}}[x_1,\cdots,x_n]\). Then the fixed subring A G has finite global dimension if and only if G is generated by quasi-reflections. In this case the fixed subring A G is isomorphic to a skew polynomial ring with possibly different p ij ’s. A version of the theorem is proved also for abelian groups acting on general quantum polynomial rings.  相似文献   

6.
周贤伟  王远允 《数学季刊》1997,12(4):98-102
1.IntroductionThemathematicalmodelofaquaduatico-1programmingproblemisasfollows:MinimizesubjecttwhereI,AsfaraspaperL1'2Jcanseemedel(I)(fordu=O)isveryimPOrtantinthemarshallingofsinglegrouptrainbetweenmarshallingstationsinrailwaynetworkandthemarshallingoftraininnetw0rkwiththetw0types0fvehiclefl0w,butproblem(I)isNP-C.C0nsiderarelax-ationproblemasf0llows:MinimizeIngeneral,solvingrelaxati0nproblemiseasierthansolvingcombinatiorial0ptimalpr0b-lem,thesameaslinearpr0grammingproblemissolvableinPOly…  相似文献   

7.
刘卓军 《数学季刊》1992,7(4):26-34
Finding all zeros of polynomial systems is very interesting and it is also useul for many applied science problems.In this paper,based on Wu‘s method,we give an algorithm to find all isolated zeros of polynomial systems (or polynomial equations).By solving Lorenz equations,it is shown that our algo-rithm is efficient and powerful.  相似文献   

8.
Branch-and-Cut algorithms for general 0–1 mixed integer programs can be successfully implemented by using Lift-and-Project (L&P) methods to generate cuts. L&P cuts are drawn from a cone of valid inequalities that is unbounded and, thus, needs to be truncated, or normalized. We consider general normalizations defined by arbitrary closed convex sets and derive dual problems for generating L&P cuts. This unified theoretical framework generalizes and covers a wide group of already known normalizations. We also give conditions for proving finite convergence of the cutting plane procedure that results from using such general L&P cuts.  相似文献   

9.
The quadratic sum-of-ratios fractional program problem has a broad range of applications in practical problems. This article will present an e?cient branch-and-bound algorithm for globally solving the quadratic sum-of-ratios fractional program problem. In this algorithm, lower bounds are computed by solving a series of parametric relaxation linear programming problems, which are established by utilizing new parametric linearizing technique. To enhance the computational speed of the proposed algorithm, a rectangle reducing tactic is used to reject a part of the investigated rectangle or the whole rectangle where there does not contain any global optimal solution of the quadratic sum-of-ratios fractional program problem. Compared with the known approaches, the proposed algorithm does not need to introduce new variables and constraints. Therefore, the proposed algorithm is more suitable for application in engineering.  相似文献   

10.
After a brief introduction to Jordan algebras, we present a primal–dual interior-point algorithm for second-order conic optimization that uses full Nesterov–Todd steps; no line searches are required. The number of iterations of the algorithm coincides with the currently best iteration bound for second-order conic optimization. We also generalize an infeasible interior-point method for linear optimization to second-order conic optimization. As usual for infeasible interior-point methods, the starting point depends on a positive number. The algorithm either finds a solution in a finite number of iterations or determines that the primal–dual problem pair has no optimal solution with vanishing duality gap.  相似文献   

11.
A new method for linearly constrained nonlinear programming is proposed. This method follows affine scaling paths defined by systems of ordinary differential equations and it is fully parallelizable. The convergence of the method is proved for a nondegenerate problem with pseudoconvex objective function. In practice, the algorithm works also under more general assumptions on the objective function. Numerical results obtained with this computational method on several test problems are shown.  相似文献   

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13.
We consider an inverse quadratic programming (QP) problem in which the parameters in the objective function of a given QP problem are adjusted as little as possible so that a known feasible solution becomes the optimal one. We formulate this problem as a minimization problem with a positive semidefinite cone constraint and its dual is a linearly constrained semismoothly differentiable (SC1) convex programming problem with fewer variables than the original one. We demonstrate the global convergence of the augmented Lagrangian method for the dual problem and prove that the convergence rate of primal iterates, generated by the augmented Lagrange method, is proportional to 1/r, and the rate of multiplier iterates is proportional to  $1/\sqrt{r}$ , where r is the penalty parameter in the augmented Lagrangian. As the objective function of the dual problem is a SC1 function involving the projection operator onto the cone of symmetrically semi-definite matrices, the analysis requires extensive tools such as the singular value decomposition of matrices, an implicit function theorem for semismooth functions, and properties of the projection operator in the symmetric-matrix space. Furthermore, the semismooth Newton method with Armijo line search is applied to solve the subproblems in the augmented Lagrange approach, which is proven to have global convergence and local quadratic rate. Finally numerical results, implemented by the augmented Lagrangian method, are reported.  相似文献   

14.
In this paper, we propose a theoretical framework of an infeasible interior-point algorithm for solving monotone linear cornplementarity problems over symmetric cones (SCLCP). The new algorithm gets Newton-like directions from the Chen-Harker-Kanzow-Smale (CHKS) smoothing equation of the SCLCP. It possesses the following features: The starting point is easily chosen; one approximate Newton step is computed and accepted at each iteration; the iterative point with unit stepsize automatically remains in the neighborhood of central path; the iterative sequence is bounded and possesses (9(rL) polynomial-time complexity under the monotonicity and solvability of the SCLCP.  相似文献   

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16.
This paper establishes a theoretical framework of infeasible Mehrotra-type predictor–corrector algorithm for nonmonotone nonlinear complementarity problems over symmetric cones which can be regarded as an extension the Mehrotra’s algorithm proposed by Salahi et al. (On Mehrotra-type predictor–corrector algorithms. SIAM J Optim 18(4):1377–1397, 2005) from nonnegative orthant to symmetric cone. The iteration complexity of the algorithm is estimated, and some numerical results are provided. The numerical results show that the algorithm is efficient and reliable.  相似文献   

17.
Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online expectation–maximization (EM) algorithm for estimating the static parameters of such models. The SMC online EM algorithm has a cost per time which is linear in the number of particles and could be particularly important when the data is representable as a long sequence of observations, since it drastically reduces the computational requirements for implementation. We present an asymptotic analysis for the stability of the SMC estimates used in the online EM algorithm and demonstrate the performance of this scheme by using both simulated and real data originating from DNA analysis. The supplementary materials for the article are available online.  相似文献   

18.
An algorithm for computing a Gr?bner basis of an ideal of polynomials whose coefficients are taken from a ring with zero divisors, is presented; such rings include \mathbb Zn\mathbb {Z}_n and \mathbb Zn[i]\mathbb {Z}_n[i], where n is not a prime number. The algorithm is patterned after (1) Buchberger’s algorithm for computing a Gr?bner basis of a polynomial ideal whose coefficients are from a field and (2) its extension developed by Kandri-Rody and Kapur when the coefficients appearing in the polynomials are from a Euclidean domain. The algorithm works as Buchberger’s algorithm when a polynomial ideal is over a field and as Kandri-Rody–Kapur’s algorithm when a polynomial ideal is over a Euclidean domain. The proposed algorithm and the related technical development are quite different from a general framework of reduction rings proposed by Buchberger in 1984 and generalized later by Stifter to handle reduction rings with zero divisors. These different approaches are contrasted along with the obvious approach where for instance, in the case of \mathbb Zn{\mathbb {Z}}_n, the algorithm for polynomial ideals over \mathbb Z{\mathbb {Z}} could be used by augmenting the original ideal presented by polynomials over \mathbb Zn{\mathbb {Z}}_n with n (similarly, in the case of \mathbb Zn[i]{\mathbb {Z}}_n[i], the original ideal is augmented with n and i2 + 1).  相似文献   

19.
We develop an online actor–critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.  相似文献   

20.
The existence of saddle point of the Lagrange function for a convex programming problem in Banach spaces ordered by a cone with empty interior is established under a strong simultaneity condition. As a consequence, the Kuhn–Tucker conditions are derived. It is shown that the Slater and the strong simultaneity condition are equivalent if the cone determining the partial order has an interior.  相似文献   

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