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ABSTRACT Operational Research & Management Science has been defined as the field that provides analytical methodologies to make better decisions. It offers an ample set of tools to facilitate the analysis of complex organisational issues and enlighten decision-making. Nonetheless, it has also been argued that the role it actually plays for corporate strategic decisions is not as key as one would expect it. This article aims at exploring the role that OR/MS plays at the corporate level of a sample of Colombian organisations.To this end, primary information was collected through an online survey that sought to identify the various types of problems they commonly face, the tools mostly employed, and the processes they normally follow. The results suggest limited use of tools at the corporate level of the organisations surveyed. We conclude the paper with some reflections and recommendations for reversing this situation that are worthy of further research.

Resumo em Inglês:

ABSTRACT Cross docking is a form of operating break-bulk freight terminals in which the receiving products are not stocked but, instead, the incoming cargo is internally transferred to be immediately shipped in distribution trucks. With this approach, inventory costs and lead-times are significantly reduced. In this work, an approximate, continuous, non-stationary queueing model is established to estimate the number of cargo discharging doors in the receiving dock. Since the traditional first-come, first-served queueing discipline is not applicable to this specific problem, an alternative formulation, called least-distance, firstserved queue discipline, is adopted and analysed with a simulation approach. The problem is modelled to support a preliminary design of a cross-dock terminal. The objective function, to be minimized, is the sum of the rent cost of the terminal facility, the waiting cost of inbound trailers when being attended at the terminal, and the cost of handling and moving freight inside the terminal.

Resumo em Inglês:

ABSTRACT This paper deals with a problem that Information Technology outsourcing suppliers generally face when selecting a working team technically capable for specific roles in software development projects. A combination of methodologies, interactively integrated, is proposed. They are Soft System Methodology to structure the problem, Repertory Grid for individual interviews and elicitation of the selection criteria, DRV Processes to assess the candidates and to generate knowledge and consensus on the selection process and Linear Programming to assign people to each position. This multimethodology allowed finding a more comprehensive solution than that initially requested by the company, since it helped to establish the necessary transformations for the selection model to operate in the right way, set the competencies to be considered as selection criteria, develop a consensus estimate of the weighted criteria, and award global values to candidates, optimizing the assignment of roles in the group for the project.

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ABSTRACT In this article we assess the effect of market imperfections and income inequality on rural production efficiency. The analysis is carried out using the notion of stochastic conditional efficiency computed in terms of free disposal hull (FDH) efficiency measurements. Free disposal hull and conditional FDH are output oriented with variable returns to scale. They are evaluated for rural production at the county level, considering the rank of rural gross income as the output and the ranks of land expenses, labor expenses, and expenses on other technological factors as inputs. The conditional frontier is dependent on income inequality and other indicators related to market imperfections. The econometric approach is based on fractional regression models and the generalized method of moments (GMM). Overall, the market imperfection variables act to reduce performance, and income dispersion is positively associated with technical efficiency.

Resumo em Inglês:

ABSTRACT The Brazilian electricity energy matrix is essentially formed by hydraulic sources which currently account for 70% of the installed capacity. One of the most important characteristics of a generation system with hydro predominance is the strong dependence on the inflow regimes. Nowadays, the Brazilian power sector uses the PAR(p) model to generate scenarios for hydrological inflows. This approach does not consider any exogenous information that may affect hydrological regimes. The main objective of this paper is to infer on the influence of climatic events in water inflows as a way to improve the model’s performance. The proposed model is called “causal PAR(p)” and considers exogenous variables, such as El Niño and Sunspots, to generate scenarios for some Brazilian reservoirs. The result shows that the error measures decrease approximately 3%. This improvement indicates that the inclusion of climate variables to model and simulate the inflows time series is a valid exercise and should be taken into consideration.

Resumo em Inglês:

ABSTRACT This paper presents the evaluation of a daily inflow forecasting model using a tool that facilitates the analysis of mathematical models for hydroelectric plants. The model is based on a Fuzzy Inference System. An offline version of the Expectation Maximization algorithm is employed to adjust the model parameters. The tool integrates different inflow forecasting models into a single physical structure. It makes uniform and streamlines the management of data, prediction studies, and presentation of results. A case study is carried out using data from three Brazilian hydroelectric plants of the Parana basin, Tiete River, in southern Brazil. Their activities are coordinated by Operator of the National Electric System (ONS) and inspected by the National Agency for Electricity (ANEEL). The model is evaluated considering a multi-step ahead forecasting task. The graphs allow a comparison between observed and forecasted inflows. For statistical analysis, it is used the mean absolute percentage error, the root mean square error, the mean absolute error, and the mass curve coefficient. The results show an adequate performance of the model, leading to a promising alternative for daily inflow forecasting.

Resumo em Inglês:

ABSTRACT This work analyzed different logistics structures under a sustainable perspective. It wasdeveloped a discrete event simulation model associated with optimization algorithm to evaluate the best combinations of the model. Besides, the comparison between the simulation optimization and a multicriteria method was performed. The simulation software Ururau, in which a model with optimization algorithm allowed testing different variables, was applied in order to find the best answer to the issue. Results showed that a connection of direct proportionality between variables of transport time, greenhouse gas emissions and lead time can happen. It was also checked that the solution returned by the simulation optimization was similar to the multicriteria method in most of the tests. The ones that differed were due to smallmathematical precisions between the methods.

Resumo em Inglês:

ABSTRACT The proposed study is related to the identification of important factors that determine the feasibility of regional airport hubs in São Paulo State, Brazil. This way, new perspectives are created to map airports in this region based on economic criteria of operations and volumes. The study is based on statistical data analysis of time series related to operations and volume of passengers and cargo transport data sets during a fixed period of time. Stochastic volatility models are applied for the logarithmic transformed counting data set considering the four largest airports selected from a group of 32 airports in the São Paulo State chosen by their importance in the amount of passenger and cargo for the period ranging from the year 2008 to the year 2014. This study is a new approach in the analysis of air transport time series.

Resumo em Inglês:

ABSTRACT This study compares the optimal control model and stochastic quadratic programming (SQP) model of a production-inventory system. A single product, without shortage in the case of a periodic-review policy with stochastic demand and deterioration rate as a function of time, is discussed. The items are subjected to deterioration via storage and the inventory goal level as a function of production. Demand isrepresented by a stochastic differential equation, converted to a stochastic constraint, and then to a deterministic constraint. We derive the optimality conditions of optimal control model and formulate three models of SQP. The effect of stochastic demand on the production rate and inventory level is then illustrated. Our numerical results appear to suggest that control of inventory level is better in the case of SQP. Furthermore, the total cost is similar in the three models of SQP - despite a difference in production rates and inventory levels.