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1.
A. Foussats C. Repetto O. P. Zandron O. S. Zandron 《International Journal of Theoretical Physics》2002,41(6):1053-1082
In order to describe the dynamics of the t–J model, two different families of first-order Lagrangians in terms of the generators of the Hubbard algebra are found. Such families correspond to different dynamical second-class constrained systems. The quantization is carried out by using the path-integral formalism. In this context the introduction of proper ghost fields is needed to render the model renormalizable. In each case the standard Feynman diagrammatics is obtained and the renormalized physical quantities are computed and analyzed. In the first case a nonperturbative large-N expansion is considered with the purpose of studying the generalized Hubbard model describing N-fold-degenerate correlated bands. In this case the 1/N correction to the renormalized boson propagator is computed. In the second case the perturbative Lagrangian formalism is developed and it is shown how propagators and vertices can be renormalized to each order. In particular, the renormalized ferromagnetic magnon propagator coming from our formalism is studied in details. As an example the thermal softening of the magnon frequency is computed. The antiferromagnetic case is also analyzed, and the results are confronted with previous one obtained by means of the spin-polaron theories. 相似文献
2.
3.
M. A. Diniz-Ehrhardt M. A. Gomes-Ruggiero J. M. Martínez S. A. Santos 《Journal of Optimization Theory and Applications》2004,123(3):497-517
The spectral projected gradient method SPG is an algorithm for large-scale bound-constrained optimization introduced recently by Birgin, Martínez, and Raydan. It is based on the Raydan unconstrained generalization of the Barzilai-Borwein method for quadratics. The SPG algorithm turned out to be surprisingly effective for solving many large-scale minimization problems with box constraints. Therefore, it is natural to test its perfomance for solving the sub-problems that appear in nonlinear programming methods based on augmented Lagrangians. In this work, augmented Lagrangian methods which use SPG as the underlying convex-constraint solver are introduced (ALSPG) and the methods are tested in two sets of problems. First, a meaningful subset of large-scale nonlinearly constrained problems of the CUTE collection is solved and compared with the perfomance of LANCELOT. Second, a family of location problems in the minimax formulation is solved against the package FFSQP. 相似文献
4.
L. Contesse-Becker 《Journal of Optimization Theory and Applications》1993,79(2):273-310
In this paper, we extend the classical convergence and rate of convergence results for the method of multipliers for equality constrained problems to general inequality constrained problems, without assuming the strict complementarity hypothesis at the local optimal solution. Instead, we consider an alternative second-order sufficient condition for a strict local minimum, which coincides with the standard one in the case of strict complementary slackness. As a consequence, new stopping rules are derived in order to guarantee a local linear rate of convergence for the method, even if the current Lagrangian is only asymptotically minimized in this more general setting. These extended results allow us to broaden the scope of applicability of the method of multipliers, in order to cover all those problems admitting loosely binding constraints at some optimal solution. This fact is not meaningless, since in practice this kind of problem seems to be more the rule rather than the exception.In proving the different results, we follow the classical primaldual approach to the method of multipliers, considering the approximate minimizers for the original augmented Lagrangian as the exact solutions for some adequate approximate augmented Lagrangian. In particular, we prove a general uniform continuity property concerning both their primal and their dual optimal solution set maps, a property that could be useful beyond the scope of this paper. This approach leads to very simple proofs of the preliminary results and to a straight-forward proof of the main results.The author gratefully acknowledges the referees for their helpful comments and remarks. This research was supported by FONDECYT (Fondo Nacional de Desarrollo Científico y Technológico de Chile). 相似文献
5.
The Dantzig-Wolfe reformulation principle is presented based on the concept of generating sets. The use of generating sets allows for an easy extension to mixed integer programming. Moreover, it provides a unifying framework for viewing various column generation practices, such as relaxing or tightening the column generation subproblem and introducing stabilization techniques. 相似文献
6.
Regina S. Burachik Rafail N. Gasimov Nergiz A. Ismayilova C. Yalçin. Kaya 《Journal of Global Optimization》2006,34(1):55-78
We study convergence properties of a modified subgradient algorithm, applied to the dual problem defined by the sharp augmented
Lagrangian. The primal problem we consider is nonconvex and nondifferentiable, with equality constraints. We obtain primal
and dual convergence results, as well as a condition for existence of a dual solution. Using a practical selection of the
step-size parameters, we demonstrate the algorithm and its advantages on test problems, including an integer programming and
an optimal control problem.
*Partially Supported by 2003 UniSA ITEE Small Research Grant Ero2.
Supported by CAPES, Brazil, Grant No. 0664-02/2, during her visit to the School of Mathematics and Statistics, UniSA. 相似文献
7.
Augustine O. Esogbue Qiang Song Donovan Young 《Mathematical Methods of Operations Research》2006,63(3):525-542
In this paper the problem of verifying the Pareto-optimality of a given solution to a dynamic multiple-criterion decision (DMCD) problem is investigated. For this purpose, some new conditions are derived for Pareto-optimality of DMCD problems. In the literature, Pareto-optimality is characterized by means of Euler-Lagrangian differential equations. There exist problems in production and inventory control to which these conditions cannot be applied directly (Song 1997). Thus, it is necessary to explore new conditions for Pareto-optimality of DMCD problems. With some mild assumptions on the objective functionals, we develop necessary and/or sufficient conditions for Pareto-optimality in the sprit of optimization theory. Both linear and non-linear cases are considered. 相似文献
8.
9.
A new parallel storm surge model, the Parallel Environmental Model (PEM), is developed and tested by comparisons with analytic solutions. The PEM is a 2‐D vertically averaged, wetting and drying numerical model and can be operated in explicit, semi‐implicit and fully implicit modes. In the implicit mode, the propagation, Coriolis and bottom friction terms can all be treated implicitly. The advection and diffusion terms are solved with a parallel Eulerian–Lagrangian scheme developed for this study. The model is developed specifically for use on parallel computer systems and will function accordingly in either explicit of implicit modes. Storm boundary conditions are based on a simple exponential decay of pressure from the centre of a storm. The simulated flooding caused by a major Category 5 hurricane making landfall in the Indian River Lagoon, Florida is then presented as an example application of the PEM. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
10.
Satoru Ibaraki Masao Fukushima Toshihide Ibaraki 《Computational Optimization and Applications》1992,1(2):207-226
A primal-dual version of the proximal point algorithm is developed for linearly constrained convex programming problems. The algorithm is an iterative method to find a saddle point of the Lagrangian of the problem. At each iteration of the algorithm, we compute an approximate saddle point of the Lagrangian function augmented by quadratic proximal terms of both primal and dual variables. Specifically, we first minimize the function with respect to the primal variables and then approximately maximize the resulting function of the dual variables. The merit of this approach exists in the fact that the latter function is differentiable and the maximization of this function is subject to no constraints. We discuss convergence properties of the algorithm and report some numerical results for network flow problems with separable quadratic costs. 相似文献