Resumo em Inglês:

ABSTRACT Time metrics are extremely important to evaluate the transmission performance on Wireless Mesh Networks (WMNs), whose main characteristic is to use multihop technology to extend the network coverage area. One of such metrics is WCETT (Weighted Cumulative Expected Transmission Time), in which transmission times per hop are weighted for both proactive and reactive conditions. Furthermore, such metrics are able to detect delays that can degrade some network services. This paper presents an optimization model to minimize WCETT in a WMN, subject to constraints grouped by bandwidth, flow control and power control. As the model includes nonlinear constraints, we propose a heuristic to solve it, which divides the problem in two subproblems. The first subproblem maximizes the network link capacity and a Simulated Annealing algorithm is used to solve it. Considering the link capacities obtained, the second subproblem minimizes the WCETTs, which is formulated as a linear programming model. Some numerical results are presented, based on instances of WMNs randomly generated. Some of these results are compared with the results obtained by a commercial simulator in order to verify the coherence of the proposed heuristic for realistic scenarios.

Resumo em Inglês:

ABSTRACT Critical Care is a medical specialty which addresses the life-saving and lifesustaining management of patients at risk of imminent death. The number of Intensive Care Unit (ICU) beds has an impact on patient’s prognosis. This paper aims to determine the optimal number of ICU beds to reduce patient’s waiting time. Time series was applied to predict demand making use of information on the daily patient’s requests for ICU beds to obtain a demand forecast by means of exponential smoothing and Box-Jenkins models, which provided the input of a Queuing model. The outputs were the optimal number of ICU beds, in different scenarios, based on demand rate and patient’s length of stay (LOS). A maximum waiting time in the queue of 6 hours was proposed and compared to government recommendation (118-353 beds). The need for ICU beds varied from 345 to 592 for a 6-hour waiting time (for a LOS of 6.5 to 11.2 days, respectively). The results show that managing demand and discharge timing could control the queue. Moreover, they also suggest that the current recommendation is inadequate for the demand.

Resumo em Inglês:

ABSTRACT Here, we propose a novel methodology for replenishment and control systems for inventories of two-echelon logistics networks using a two-stage stochastic programming, considering periodic review and uncertain demands. In addition, to achieve better customer services, we introduce a variable rationing rule to address quantities of the item in short. The devised models are reformulated into their deterministic equivalent, resulting in nonlinear mixed-integer programming models, which are then approximately linearized. To deal with the uncertain nature of the item demand levels, we apply a Monte Carlo simulation-based method to generate finite and discrete sets of scenarios. Moreover, the proposed approach does not require restricted assumptions to the behavior of the probabilistic phenomena, as does several existing methods in the literature. Numerical experiments with the proposed approach for randomly generated instances of the problem show results with errors around 1%.

Resumo em Inglês:

ABSTRACT In this article, we have built a co-authorship network among researchers with CNPQ grant in research productivity (PQ) in the area of Industrial Engineering and analyze which Social Network Analysis metrics impact their productivity level. Unlike other studies that mostly analyze unweighted networks, ours explored more broadly the network since the metrics were calculated in three ways: unweighted, including the edges weights and including the edges and nodes’ attributes. Thus, the generated results are more precise and detailed since more information is obtained. We consider the h-index of the researchers as the nodes’ attributes and measured the impact using Kendall correlation. We show that geographical distance is still a barrier to collaboration among PQs in this area and that collaboration with researchers with different levels of grant has the greatest impact in the level of the grant a researcher has.

Resumo em Inglês:

ABSTRACT This paper addresses a lot sizing problem in a Brazilian chemical industry where a product can be produced by more than one process, which can use different parallel machines and may even consume a wide range of raw materials. Moreover, most of the products are liquids and the inventories must be kept in a restricted number of storage tanks with a limited capacity. Hence, these two issues are barely addressed in the literature on lot sizing. The classical multi-level capacitated lot sizing problem was extended to address them and a mixed integer programming (MIP) formulation was developed to determine how many batches should be produced and in which tank products should be stored to meet the demands and minimize production costs. The results of computational experiments show that the commercial solver found poor quality solutions or could not find feasible solutions within one hour. Thus, we applied relaxand-fix and fix-and-optimize MIP based heuristics and we observed that these heuristics were able to obtain feasible solutions for more instances in shorter computational times and find better solutions than those obtained by the commercial solver to solve the proposed model.

Resumo em Inglês:

ABSTRACT This article aims to analyze the technical performance of football teams in the FA Premier League during the 2015/2016 season. Data of twenty clubs over 38 matches for each club are considered using 23 variables. These variables have been explored in the football literature and address different features of technical performance. The different configuration of the data for teams in detached segments motivated the multi-criteria approach, which enables identification of strong and weak sectors in each segment. The uncertainty as to the outcome of football matches and the imprecision of the measures indicated the use of Composition of Probabilistic Preferences (CPP) to model the problem. “R” software was used in the modeling and computation. The CPP global scores obtained were more consistent with the final classification than those of other methods. CPP scores revealed different performances of particular groups of variables indicating aspects to be improved and explored.

Resumo em Inglês:

ABSTRACT In this paper, we discuss computational aspects to obtain accurate inferences for the parameters of the generalized gamma (GG) distribution. Usually, the solution of the maximum likelihood estimators (MLE) for the GG distribution have no stable behavior depending on large sample sizes and good initial values to be used in the iterative numerical algorithms. From a Bayesian approach, this problem remains, but now related to the choice of prior distributions for the parameters of this model. We presented some exploratory techniques to obtain good initial values to be used in the iterative procedures and also to elicited appropriate informative priors. Finally, our proposed methodology is also considered for data sets in the presence of censorship.

Resumo em Inglês:

ABSTRACT The Vehicle Routing Problem (VRP) is a classical problem, and when the number of customers is very large, the task of finding the optimal solution can be extremely complex. It is still necessary to find an effective way to evaluate the quality of solutions when there is no known optimal solution. This work presents a suggestion to analyze the quality of vehicle routes, based only on their geometric properties. The proposed descriptors aim to be invariants in relation to the amount of customers, vehicles and the size of the covered area. Applying the methodology proposed in this work it is possible to obtain the route and, then, to evaluate the quality of solutions obtained using computer vision. Despite considering problems with different configurations for the number of customers, vehicles and service area, the results obtained with the experiments show that the proposal is useful for classifying the routes into good or bad classes. A visual analysis was performed using the Parallel Coordinates and Viz3D techniques and then a classification was performed by a Backpropagation Neural Network, which indicated an accuracy rate of 99.87%.

Resumo em Inglês:

ABSTRACT We propose a model and solution method to a simultaneous route design and frequency setting problem on a main corridor from one of the Bus Rapid Transit (BRT) Systems of Colombia. The proposed model considers objectives of users and operators in a combinatorial multi-objective optimization framework and takes into account real constraints on the operation of some Colombian BRT systems not found in previous models. The problem is solved heuristically by a Genetic Algorithm which is tailored from an existing work, to consider specific characteristics of the real scenario. The methodology is validated with current data from one of the most important bus corridors in a Colombian BRT system. The results obtained improve the current solutions for this corridor.