A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A smooth evolutionary structural optimization procedure applied to plane stress problem

Topological optimization problems based on stress criteria are solved using two techniques in this paper. The first technique is the conventional Evolutionary Structural Optimization (ESO), which is known as hard kill, because the material is discretely removed; that is, the elements under low stress that are being inefficiently utilized have their constitutive matrix has suddenly reduced. The second technique, proposed in a previous paper, is a variant of the ESO procedure and is called Smooth ESO (SESO), which is based on the philosophy that if an element is not really necessary for the structure, its contribution to the structural stiffness will gradually diminish until it no longer influences the structure; its removal is thus performed smoothly. This procedure is known as "soft-kill"; that is, not all of the elements removed from the structure using the ESO criterion are discarded. Thus, the elements returned to the structure must provide a good conditioning system that will be resolved in the next iteration, and they are considered important to the optimization process. To evaluate elasticity problems numerically, finite element analysis is applied, but instead of using conventional quadrilateral finite elements, a plane-stress triangular finite element was implemented with high-order modes for solving complex geometric problems. A number of typical examples demonstrate that the proposed approach is effective for solving problems of bi-dimensional elasticity. (C) 2014 Elsevier Ltd. All rights reserved.

Evolutionary trends in Iridaceae: new cytogenetic findings from the New World

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Perception of brazilian citizens about Darwinism and the (Non) Influence of God in the evolutionary process

The current context is unique in relation to the teaching of evolution in Brazil and the population's perception of evolution. On the one hand, it is said often about Darwinism in various media, especially due to the relatively recent commemoration of the two hundred years of the birth of Charles Darwin and one hundred and fifty years of the launch of the book The Origin of Species. On the other hand, it is clear, in recent years, a timid movement, more worryingly, in favor of equitable approach of creationist and evolutionist theories in the classroom. This article is a part of a research whose goal is to raise the design that Brazilian respondents have about the Darwinian view (which disregards the divine influence in the evolution of the species). The instrument used for data collection is a questionnaire, type Likert scale, which consists of a series of statements in which respondents must express their degree of agreement or disagreement with each statement. In this study, we present the results of the statement. "The thought of Darwin, which does not consider God as a participant in the process of evolution, is...". Analysis correlated with data on religion and education of the respondents are also held. The results point to a tendency of respondents not to accept the Darwinian view that disregards God's interference in the evolutionary process. The data also show that respondents' choices are influenced by religion and education. The frequency of responses that tend to accept the Darwinian view (which disregards the divine participation in the evolution of the species) is higher among respondents with higher levels of education. Adherents to religions "evangelical" tend to deny this view more often than followers of other religions. Given the potential risks of inserting creationist approaches in school education, it is necessary a discussion of the possible impacts of this rejection of Darwin's thinking (which does not consider God as a participant in the evolutionary process), indicated here, in the teaching of evolution. This work was supported by FAPEMIG.

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

A comparison about evolutionary algorithms for optimum-path forest clustering optimization

In this paper we deal with the problem of boosting the Optimum-Path Forest (OPF) clustering approach using evolutionary-based optimization techniques. As the OPF classifier performs an exhaustive search to find out the size of sample's neighborhood that allows it to reach the minimum graph cut as a quality measure, we compared several optimization techniques that can obtain close graph cut values to the ones obtained by brute force. Experiments in two public datasets in the context of unsupervised network intrusion detection have showed the evolutionary optimization techniques can find suitable values for the neighborhood faster than the exhaustive search. Additionally, we have showed that it is not necessary to employ many agents for such task, since the neighborhood size is defined by discrete values, with constrain the set of possible solution to a few ones.