Resumo em Inglês:

A well-known traffic simulation model bases on the idea to represent street sections by so-called cells where vehicles are streaming from one cell to another in order to give a realistic image of traffic flows. Its basic ideas were picked up recently to formulate an optimization model for evacuationplanning purposes. We will address three major weaknesses of the recent model, namely the usage of afixed single cell size, missing consideration of lanes as well as missing limitations for traffic flows andshow how to overcome them. Stimulated by this, we formulate the extended Cell-Transmission-Based Evacuation Planning Model and a new optimization model to facilitate this model in terms of choosing the optimum cell size. Additionally, we will present an iterative simulation-based optimization approach in order to evaluate and to enhance results in a more realistic environment. This approach takes advantage of a standalone vehicle reallocation optimization model, additional traffic flow limitations as well as a state-of-the-art microscopic traffic simulation. We will demonstrate the effectiveness of this approach in a real-world example.

Resumo em Inglês:

Management of the operations in a copper smelter is fundamental for optimizing the use of the plant's installed capacity. In the refining and casting stage, the operations are particularly complex due to the metallurgical characteristics of the process. This paper tackles the problem of automatic scheduling of operations in the refining and casting stage of a copper concentrate smelter. The problem is transformed into a flexible flow shop problem and to solve it, an iterative method is proposed that operates in two stages: in the first stage, a sequence of jobs is constructed that configures the lots, and in the second, the constructed solution is improved by means of simulated annealing. Fifteen test problems are used to show that the proposed algorithm improves the makespan by an average of 9.42% and the mean flow time by 12.19% with respect to an existing constructive heuristic.

Resumo em Inglês:

Two ordinal logit models are applied to fit the results of matches in the Brazilian football championship. As explanatory variables are employed measures of previous performance of the teamsalong all preceding games, along recent games and when playing at home and as a visitor. The results of the models adjustment are employed in simulations performed to forecast the number of points to be earnedin the following games and to anticipate the teams' final classification.

Resumo em Inglês:

An increasingly competitive market means that many decisions must be taken, quickly and with precision, in complex, high risk scenarios. This combination of factors makes it necessary to use decision aiding methods which provide a means of dealing with uncertainty in the judgement of the alternatives. This work presents the use of the MAUT method, combined with the INTERVAL SMART/SWING WEIGHTING method. Although multicriteria decision aiding was not conceived specifically for tackling uncertainty, the combined use of MAUT and the INTERVAL SMART/SWING WEIGHTING method allows approaching decision problems under uncertainty. The main concepts which are involved in these two methods are described and their joint application to the case study concerning the selection of a printing service supplier is presented. The case study makes use of the WINPRE software as a support tool for the calculation of dominance. It is then concluded that the proposed approach can be applied to decision making problems under uncertainty.

Resumo em Inglês:

The periodic autoregressive model, a particular structure of the Box & Jenkins family, denoted by PAR (p), is employed to model the series of hydrological streamflow used for estimating the operational costs of the Brazilian hydro-thermal optimal dispatch. Recently, some aspects of this approachbegan to be studied and several researches on this topic are being developed. This paper focuses on the identification stage of the orders p of these models. Nowadays, the identification is based on evaluating the significance of the coefficients of the partial autocorrelation function (PACF), based on the asymptoticresults of Quenouille. The purpose of this study is on the application of the computer-intensive Bootstraptechnique to estimate the significance of such coefficients. The results show that identification via Bootstrap is considerably more parsimonious, leading to the identification of lower orders in most cases andcorroborating some points raised in previous studies on the traditional approach.

Resumo em Inglês:

This paper approaches the algorithm of selection of variables named MIFS-U and presents an alternative method for estimating entropy and mutual information, "measures" that constitute the base of this selection algorithm. This method has, for foundation, the Cauchy-Schwartz quadratic mutual information and the Rényi quadratic entropy, combined, in the case of continuous variables, with Parzen Window density estimation. Experiments were accomplished with public domain data, being such method compared with the original MIFS-U algorithm, broadly used, that adopts the Shannon entropy definition and makes use, in the case of continuous variables, of the histogram density estimator. The results show small variations between the two methods, what suggest a future investigation using a classifier, such as Neural Networks, to qualitatively evaluate these results, in the light of the final objective which is greater accuracy of classification.

Resumo em Inglês:

The purpose of this study is to verify the efficiency and the applicability of the Least-Squares Monte Carlo method for pricing American interest rate options. Results suggest that this technique is apromising alternative to evaluate American-style interest rate options. It provides accurate option price estimates which are very close to results provided by a binomial model. Besides, actual implementation can be easily adapted to accept different interest rate models.

Resumo em Inglês:

This article presents a tutorial on mixture-process experiments and a case study of a chemical compound used in the delay mechanism for starting a rocket engine. The compound consists in a three-component mixture. Besides the mixture components, two process variables are considered. For the model selection, the use of an information criterion showed to be efficient in the case under study. A linear regression model was fitted. Through the developed model, the optimal proportions of the mixture components and the levels of the process variables were determined.

Resumo em Inglês:

A radiotherapy planning is considered optimal when all the parameters involved, physical or biological, have been investigated and appropriate for each patient. In this type of planning, the major concern is with the tumor irradiation with the minimum possible damage to healthy tissues of the irradiated region, especially the organs at risk. The optimal planning for radiotherapy can be aided by Linear Programming and there is a wide literature addressing this subject. However, most published mathematical formulations do not contemplate a scenario in terms of practical applications, because they do not incorporate the heterogeneous composition of the irradiated tissue. This paper presents a methodology for heterogeneity correction in the composition of different types of irradiated tissues based on proportions among their different linear attenuation coefficient.

Resumo em Inglês:

This article presents improvements to the hybrid preconditioner previously developed for the solution through the conjugate gradient method of the linear systems which arise from interior-point methods. The hybrid preconditioner consists of combining two preconditioners: controlled Cholesky factorization and the splitting preconditioner used in different phases of the optimization process. The first, with controlled fill-in, is more efficient at the initial iterations of the interior-point methods and it may be inefficient near a solution of the linear problem when the system is highly ill-conditioned; the second is specialized for such situation and has the opposite behavior. This approach works better than direct methods for some classes of large-scale problems. This work has proposed new heuristics for the integration of both preconditioners, identifying a new change of phases with computational results superior to the ones previously published. Moreover, the performance of the splitting preconditioner has been improved through new orderings of the constraint matrix columns allowing savings in the preconditioned conjugate gradient method iterations number. Experiments are performed with a set of large-scale problems and both approaches are compared with respect to the number of iterations and running time.

Resumo em Inglês:

In this paper, a decision problem involving a car parts manufacturing company is modeled in order to prepare the company for an increase in demand. Mixed-integer linear programming was used with the following decision variables: creating a second shift, purchasing additional equipment, determining the required work force, and other alternatives involving new manners of work distribution that make it possible to separate certain operations from some workplaces and integrate them into others to minimize production costs. The model was solved using GAMS. The solution consisted of programming 19 workers under a configuration that merges two workplaces and separates some operations from some workplaces. The solution did not involve purchasing additional machinery or creating a second shift. As a result, the manufacturing paradigms that had been valid in the company for over 14 years were broken. This study allowed the company to increase its productivity and obtain significant savings. It also shows the benefits of joint work between academia and companies, and provides useful information for professors, students and engineers regarding production and continuous improvement.