Resumo em Inglês:

In this paper, a general scheme for generating extra cuts during the execution of a Benders decomposition algorithm is presented. These cuts are based on feasible and infeasible master problem solutions generated by means of a heuristic. This article includes general guidelines and a case study with a fixed charge network design problem. Computational tests with instances of this problem show the efficiency of the strategy. The most important aspect of the proposed ideas is their generality, which allows them to be used in virtually any Benders decomposition implementation.

Resumo em Inglês:

In recent years, a lot of work has been done dealing with alternative performance rankings for the Olympic Games. Almost all of these works use Data Envelopment Analysis (DEA). Generally speaking, those works can be divided into two categories: Pure rankings with unitary input models and relative rankings with classical DEA models; both output oriented. In this paper we introduce an approach taking into account the number of athletes as a proxy to the country investment in sports. This number is an input for a DEA model, and the other input is the population of the country. We have three outputs,the number of gold, silver and bronze medals earned by each country. Contrary to the usual approach in the literature, our model is not output oriented. It is a non-radial DEA model oriented to the "number of athletes" input, as our goal is not a countries' ranking. We intend to analyse whether the number of athletes competing for each country accords with the number of won medals. For this analysis, we compare eachcountry with its benchmarks. The Decision Making Units (DMU) are all the countries participating in the Beijing Olympic Games, including those that did not earn a single medal. We use a BCC model and we compare each DMU's target with the number of athletes who have won, at least one medal.

Resumo em Inglês:

The main objective of this article is to develop a transparent and efficient model, using the AHP (Analytic Hierarchy Process) method as a basis and applying the software SuperDecisions, which makes it possible to evaluate the performance of employees, aligning the individual objectives defined and the competences required for the organisational mission. The methodology used was of an investigative and exploratory nature, due to the need to increase knowledge on the use of the AHP in the process of classifying employee performance. Starting from a high performance culture, it is possible to highlight the employees who present the best performance and improve the remuneration policies, as well as invest in the training of the skills lacking in a clear and assertive manner. The results found in this research prove the viability of the respective application, which is directly related to the meeting of targets and, consequently,to sustaining competitiveness and increasing added value for shareholders.

Resumo em Inglês:

Governments of many developing countries are presently granting concessions to private organizations to operate container terminals. A key element in this process is the technical and economic evaluation of the project. In practice, the demand levels over time are volatile. The first part of the paper deals with a capacity expansion problem with stochastic demand. Next, an optimization model employs a dynamic programming routine to find the best epochs to install new berths. Ship waiting times are computed with queuing models and are introduced into the main model as upper restrictions based on international practice. Finally, a real options analysis is performed with the objective of evaluating the effects of an eventual abandonment of the project at a pre-defined time horizon. The model is then applied to the container terminal of the Port of Rio Grande, Brazil.

Resumo em Inglês:

AHP has been successful in many cases but it has a major limitation: a larger number of alternatives requires a high number of judgements in the comparison matrices. In order to reduce this problem,we present a method with clusters and pivots. This method also helps with a further four problems of the Analytic Hierarchy Process. It enlarges the comparison scale, facilitates the construction of a consistent or near consistent matrix, eliminates the problem of the choice of the priorities derivation method and allows the use of incomparable alternatives.

Resumo em Inglês:

Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.

Resumo em Inglês:

The goal of the capacitor allocation problem in radial distribution networks is to minimize technical losses with consequential positive impacts on economic and environmental areas. The main objective is to define the size and location of the capacitors while considering load variations in a given horizon. The mathematical formulation for this planning problem is given by an integer nonlinear mathematical programming model that demands great computational effort to be solved. With the goal of solving this problem, this paper proposes a methodology that is composed of heuristics and Tabu Search procedures. The methodology presented explores network system characteristics of the network system reactive loads for identifying regions where procedures of local and intensive searches should be performed. A description of the proposed methodology and an analysis of computational results obtained which are based on several test systems including actual systems are presented. The solutions reached are as good as or better than those indicated by well referenced methodologies. The technique proposed is simple in its use and does not require calibrating an excessive amount of parameters, making it an attractive alternative for companies involved in the planning of radial distribution networks.

Resumo em Inglês:

The database of real world contains a huge volume of data and among them there are hidden piles of interesting relations that are actually very hard to find out. The knowledge discovery in databases (KDD) appears as a possible solution to find out such relations aiming at converting information into knowledge. However, not all data presented in the bases are useful to a KDD. Usually, data are processed before being presented to a KDD aiming at reducing the amount of data and also at selecting more relevant data to be used by the system. This work consists in the use of Rough Sets Theory, in order to pre-processing data to be presented to Self-Organizing Map neural network (Hybrid Architecture) for clusters analysis. Experiments' results evidence the better performance using the Hybrid Architecture than Self-Organizing Map. The paper also presents all phases of the KDD process.

Resumo em Inglês:

This paper introduces a new variable depth search method for the Quadratic Assignment Problem. The new method considers the cost of edges assignment as the criterion to decide which vertices to exchange during local search moves. It also presents the results of an extensive experimental study that compares the performance of local search and variable depth search algorithms for the Quadratic Assignment Problem. The investigation presented here contributes to a better understanding of the potential of these techniques, which are widely used as intensification tools in more sophisticated heuristic methods, such as evolutionary algorithms. Different algorithms presented in the literature were implemented and compared to the proposed methods. The results of a computational experiment with 161 benchmark instances are reported. Different statistical tests are applied in order to analyze the results provided by the experiments.

Resumo em Inglês:

In this paper, a procedure for the on-line process control of variables is proposed. This procedure consists of inspecting the m-th item from every m produced items and deciding, at each inspection, whether the process is out-of-control. Two sets of limits, warning (µ0 ± W) and control (µ0 ± C), are used. If the value of the monitored statistic falls beyond the control limits or if a sequence of h observations falls between the warning limits and the control limits, the production is stopped for adjustment; otherwise, production goes on. The properties of an ergodic Markov chain are used to obtain an expression for the average cost per item. The parameters (the sampling interval m, the widths of the warning, the control limits W and C(W < C), and the sequence length (h) are optimized by minimizing the cost function. A numerical example illustrates the proposed procedure.