Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Firm Market Performance and Volatility in a National Real Estate Sector

We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange. from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average. (C) 2011 Elsevier Inc. All rights reserved.

Agricultural commodities pricing model applied to the Brazilian sugar market

This article suggests a pricing model for commodities used to produce biofuel. The model is based on the concept that the deterministic component of the Wiener process is not constant and depends on time and exogenous variables. The model, which incorporates theory of storage, the convenience yield and the seasonality of harvests, was applied in the Brazilian sugar market. After predictions were made with the Kalman filter, the model produced results that were statistically more accurate than those returned by the two-factor model available in the literature.

Discretionary-based disclosure: evidence from the Brazilian market

The primary objective of this paper is to identify the factors that explain Brazilian companies level of voluntary disclosure. Underpinning this work is the Discretionary-based Disclosure theory. The sample is composed of the top 100 largest non-financial companies listed in the Bolsa de Valores de São Paulo (Brazilian Securities, Commodities, and Futures exchange - BOVESPA). Information was gathered from Financial Statements for the years ending in 2006, 2007, and 2008, with the use of content analysis. A disclosure framework based on 27 studies from these years was created, with a total of 92 voluntary items divided into two dimensions: economic (43) and socio-environmental (49). Based on the existing literature, a total of 12 hypotheses were elaborated and tested using a panel data approach. Results evidence that: (a) Sector and Origin of Control are statistically significant in all three models tested: economic, socio-environmental, and total; (b) Profitability is relevant in the economic model and in the total model; (c) Tobin s Q is relevant in the socio-environmental model and in the total disclosure model; (d) Leverage and Auditing Firm are only relevant in the economic disclosure model; (e) Size, Governance, Stock Issuing, Growth Opportunities and Concentration of Control are not statistically significant in any of the three models.

Applying many-body expansion aiming to make ab in initio molecular dynamics more efficient

In this present work we present a methodology that aims to apply the many-body expansion to decrease the computational cost of ab initio molecular dynamics, keeping acceptable accuracy on the results. We implemented this methodology in a program which we called ManBo. In the many-body expansion approach, we partitioned the total energy E of the system in contributions of one body, two bodies, three bodies, etc., until the contribution of the Nth body [1-3]: E = E1 + E2 + E3 + …EN. The E1 term is the sum of the internal energy of the molecules; the term E2 is the energy due to interaction between all pairs of molecules; E3 is the energy due to interaction between all trios of molecules; and so on. In Manbo we chose to truncate the expansion in the contribution of two or three bodies, both for the calculation of the energy and for the calculation of the atomic forces. In order to partially include the many-body interactions neglected when we truncate the expansion, we can include an electrostatic embedding in the electronic structure calculations, instead of considering the monomers, pairs and trios as isolated molecules in space. In simulations we made we chose to simulate water molecules, and use the Gaussian 09 as external program to calculate the atomic forces and energy of the system, as well as reference program for analyzing the accuracy of the results obtained with the ManBo. The results show that the use of the many-body expansion seems to be an interesting approach for reducing the still prohibitive computational cost of ab initio molecular dynamics. The errors introduced on atomic forces in applying such methodology are very small. The inclusion of an embedding electrostatic seems to be a good solution for improving the results with only a small increase in simulation time. As we increase the level of calculation, the simulation time of ManBo tends to largely decrease in relation to a conventional BOMD simulation of Gaussian, due to better scalability of the methodology presented. References [1] E. E. Dahlke and D. G. Truhlar; J. Chem. Theory Comput., 3, 46 (2007). [2] E. E. Dahlke and D. G. Truhlar; J. Chem. Theory Comput., 4, 1 (2008). [3] R. Rivelino, P. Chaudhuri and S. Canuto; J. Chem. Phys., 118, 10593 (2003).