A Lagrangian bound for many-to-many assignment problems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Competition between local potentials and attractive particle-particle interactions in superlattices

Naturally occuring or man-made systems displaying periodic spatial modulations of their properties on a nanoscale constitute superlattices. Such modulated structures are important both as prototypes of simple nanotechnological devices and as particular examples of emerging spatial inhomogeneity in interacting many-electron systems. Here we investigate the effect different types of modulation of the system parameters have on the ground-state energy and the charge-density distribution of the system. The superlattices are described by the inhomogeneous attractive Hubbard model, and the calculations are performed by density-functional and density-matrix renormalization group techniques. We find that modulations in local electric potentials are much more effective in shaping the system's properties than modulations in the attractive on-site interaction. This is the same conclusion we previously [M.F. Silva, N.A. Lima, A.L. Malvezzi, K. Capelle, Phys. Rev. B 71 (2005) 125130.] obtained for repulsive interactions, suggesting that it is not an artifact of a specific state, but a general property of modulated structures. (c) 2007 Elsevier Ltd. All rights reserved.

An insight into the theoretical investigation of possible piezoelectric effect in samarium titanate (SmTiO3)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Lagrangian heuristic for a class of the generalized assignment problems

A Lagrangian based heuristic is proposed for many-to-many assignment problems taking into account capacity limits for task and agents. A modified Lagrangian bound studied earlier by the authors is presented and a greedy heuristic is then applied to get a feasible Lagrangian-based solution. The latter is also used to speed up the subgradient scheme to solve the modified Lagrangian dual problem. A numerical study is presented to demonstrate the efficiency of the proposed approach. (C) 2010 Elsevier Ltd. All rights reserved.

Método do hamiltoniano termodinamicamente equivalente para sistemas de muitos corpos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Labral gland in soldiers of the neotropical termite Cornitermes cumulans (Isoptera: Termitidae: Syntermitinae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem

The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS. (C) 2010 Elsevier Ltd. All rights reserved.

The water factor in the protein-folding problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Microtensile bond strengths and scanning electron microscopic evaluation of self-adhesive and self-etch resin cements to intact and etched enamel

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Many-body system with a four-parameter family of point interactions in one dimension

We consider a four-parameter family of point interactions in one dimension. This family is a generalization of the usual delta-function potential. We examine a system consisting of many particles of equal masses that are interacting pairwise through such a generalized point interaction. We follow McGuire who obtained exact solutions for the system when the interaction is the delta-function potential. We find exact bound states with the four-parameter family. For the scattering problem, however, we have not been so successful. This is because, as we point out, the condition of no diffraction that is crucial in McGuire's method is nor satisfied except when the four-parameter family is essentially reduced to the delta-function potential.

Global analysis of the post-SNO solar neutrino data for standard and nonstandard oscillation mechanisms

What can we learn from solar neutrino observations? Is there any solution to the solar neutrino anomaly which is favored by the present experimental panorama? After SNO results, is it possible to affirm that neutrinos have mass? In order to answer such questions we analyze the current available data from the solar neutrino experiments, including the recent SNO result, in view of many acceptable solutions to the solar neutrino problem based on different conversion mechanisms, for the first time using the same statistical procedure. This allows us to do a direct comparison of the goodness of the fit among different solutions, from which we can discuss and conclude on the current status of each proposed dynamical mechanism. These solutions are based on different assumptions: (a) neutrino mass and mixing, (b) a nonvanishing neutrino magnetic moment, (c) the existence of nonstandard flavor-changing and nonuniversal neutrino interactions, and (d) a tiny violation of the equivalence principle. We investigate the quality of the fit provided by each one of these solutions not only to the total rate measured by all the solar neutrino experiments but also to the recoil electron energy spectrum measured at different zenith angles by the Super-Kamiokande Collaboration. We conclude that several nonstandard neutrino flavor conversion mechanisms provide a very good fit to the experimental data which is comparable with (or even slightly better than) the most famous solution to the solar neutrino anomaly based on the neutrino oscillation induced by mass.

Efficient linear programming algorithm for the transmission network expansion planning problem

The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.

Many-body effects in wide parabolic AlGaAs quantum wells

Photoluminescence measurements at different temperatures have been performed to investigate the optical response of a two-dimensional electron gas in n-type wide parabolic quantum wells. A series of samples with different well widths in the range of 1000-3000 A was analyzed. Many-body effects, usually observed in the recombination process of a two-dimensional electron gas, appear as a strong enhancement in the photoluminescence spectra at the Fermi level at low temperature only in the thinnest parabolic quantum wells. The suppression of the many-body effect in the thicker quantum wells was attributed to the decrease of the overlap between the wavefunctions of the photocreated holes and the two-dimensional electrons belonging to the highest occupied electron subband. (C) 2007 American Institute of Physics.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Studying properties of Lagrangian bounds for many-to-many assignment problems

Classical and modified Lagrangian bounds for the optimal value of optimization problems with a double decomposable structure are studied. For the class of many-to-many assignment problems, this property of constraints is used to design a subgradient algorithm for solving the modified dual problem. Numerical results are presented to compare the quality of classical and modified bounds, as well as the properties of the corresponding Lagrangian solutions.