Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Global optimization approach for the H2-norm model reduction problem

A branch and bound algorithm is proposed to solve the H2-norm model reduction problem for continuous-time linear systems, with conditions assuring convergence to the global optimum in finite time. The lower and upper bounds used in the optimization procedure are obtained through Linear Matrix Inequalities formulations. Examples illustrate the results.

Optimization of the mechanical properties of low-carbon steels by formation of a multiphase microstructure

In this work five methods of heat treatments are investigated in order to obtained convenient volume fractions of ferrite, bainite, martensite and retained austenite, starting with a low carbon steel and seeking the distinction of the phases, through optical microscopy. Specific chemical etching is improved. The results in tensile and fatigue tests were accomplished and the results were related with the microstructural parameters. The results show that the mechanical properties are closely related with the phases, grains size and the phases morphology. Copyright © 2001 Society of Automotive Engineers, Inc.

Optimization of neutral hydrolysis reaction of post-consumer PET for chemical recycling

The neutral hydrolysis reaction of post-consumer poly(ethylene terephthalate) in solid state was studied through the reaction of the polymer with water at the molar ratio 1:91 with autogenous pressure. Two sizes of post-consumer PET flakes and temperatures of 135 °C, 170°C and 205°C with pressures of 4.0 atm, 7.5 atm and 13.5 atm, respectively, were considered. With reaction time equal to 6h, the method reached 99% depolymerization at 205°C, 8.2% at 170 °C and 1.7% at 135°C. The reaction extension was measured by separating the terephthalic acid formed in the process and calculating by gravimetry how much material could still be reacted. Through the viscosimetry of diluted, solutions and the counting of carboxylic end groups in the remaining material from the gravimetric assay, it was possible to suggest that the reaction occurs randomly and in the whole volume of the polymeric particle and not solely on the surface. The terephthalic acid obtained and then purified was characterized by elemental analysis, magnetic nuclear resonance, size and panicle size distribution and spectrophotometry in the visible spectrum, and it was similar to the petrochemical equivalent, with purity recorded in carbon base equal to 99.9%.

A new implementation of Population Based Incremental Learning method for optimization studies in electromagnetics

To enhance the global search ability of Population Based Incremental Learning (PBIL) methods, It Is proposed that multiple probability vectors are to be Included on available PBIL algorithms. As a result, the strategy for updating those probability vectors and the negative learning and mutation operators are redefined as reported. Numerical examples are reported to demonstrate the pros and cons of the newly Implemented algorithm. ©2006 IEEE.

Global optimization for the ℋ∞-norm model reduction problem

A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Molecularly designed layer-by-layer (LbL) films to detect catechol using information visualization methods

The control of molecular architectures has been exploited in layer-by-layer (LbL) films deposited on Au interdigitated electrodes, thus forming an electronic tongue (e-tongue) system that reached an unprecedented high sensitivity (down to 10-12 M) in detecting catechol. Such high sensitivity was made possible upon using units containing the enzyme tyrosinase, which interacted specifically with catechol, and by processing impedance spectroscopy data with information visualization methods. These latter methods, including the parallel coordinates technique, were also useful for identifying the major contributors to the high distinguishing ability toward catechol. Among several film architectures tested, the most efficient had a tyrosinase layer deposited atop LbL films of alternating layers of dioctadecyldimethylammonium bromide (DODAB) and 1,2-dipalmitoyl-sn-3-glycero-fosfo-rac-(1-glycerol) (DPPG), viz., (DODAB/DPPG)5/DODAB/Tyr. The latter represents a more suitable medium for immobilizing tyrosinase when compared to conventional polyelectrolytes. Furthermore, the distinction was more effective at low frequencies where double-layer effects on the film/liquid sample dominate the electrical response. Because the optimization of film architectures based on information visualization is completely generic, the approach presented here may be extended to designing architectures for other types of applications in addition to sensing and biosensing. © 2013 American Chemical Society.

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

Construction of pediatric homogeneous phantoms for optimization of chest and skull radiographs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Perioperative fluid therapy: a statement from the international fluid optimization group

Perioperative fluid therapy remains a highly debated topic. Its purpose is to maintain or restore effective circulating blood volume during the immediate perioperative period. Maintaining effective circulating blood volume and pressure are key components of assuring adequate organ perfusion while avoiding the risks associated with either organ hypo- or hyperperfusion. Relative to perioperative fluid therapy, three inescapable conclusions exist: overhydration is bad, underhydration is bad, and what we assume about the fluid status of our patients may be incorrect. There is wide variability of practice, both between individuals and institutions. The aims of this paper are to clearly define the risks and benefits of fluid choices within the perioperative space, to describe current evidence-based methodologies for their administration, and ultimately to reduce the variability with which perioperative fluids are administered. Based on the abovementioned acknowledgements, a group of 72 researchers, well known within the field of fluid resuscitation, were invited, via email, to attend a meeting that was held in Chicago in 2011 to discuss perioperative fluid therapy. From the 72 invitees, 14 researchers representing 7 countries attended, and thus, the international Fluid Optimization Group (FOG) came into existence. These researches, working collaboratively, have reviewed the data from 162 different fluid resuscitation papers including both operative and intensive care unit populations. This manuscript is the result of 3 years of evidence-based, discussions, analysis, and synthesis of the currently known risks and benefits of individual fluids and the best methods for administering them. The results of this review paper provide an overview of the components of an effective perioperative fluid administration plan and address both the physiologic principles and outcomes of fluid administration. We recommend that both perioperative fluid choice and therapy be individualized. Patients should receive fluid therapy guided by predefined physiologic targets. Specifically, fluids should be administered when patients require augmentation of their perfusion and are also volume responsive. This paper provides a general approach to fluid therapy and practical recommendations.