Eliane Gonçalves Gomes

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It is usual to rank the participating countries in the Olympic Games in accordance with the number of medals they have won. An alternative ranking is suggested in this paper. This ranking is based on each country’s ability to win medals in relation to its available resources. This is an efficiency that can be measured with the help of Data Envelopment(More)
The introductory chapter begins with a brief introduction to data envelopment analysis (DEA) and its origin, followed by the basic assumptions. Further, the concept of efficiency is introduced, through worked examples and graphs, to researchers unfamiliar with the technique. Finally, the basic models of DEA are provided for direct reference for those(More)
This paper presents an application of the integration between Geographical Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) to aid spatial decisions. We present a hypothetical case study to illustrate the GIS–MCDA integration: the selection of the best municipal district of Rio de Janeiro State, Brazil, in relation to the quality of(More)
There is no official method to establish a final ranking for the Olympic Games. The usual ranking is based on the Lexicographic Multicriteria Method, the main drawback of which is to overvalue gold medals. Furthermore, it does not take into account the results of the Winter Games, which are also part of the Olympic Games. This paper proposes a method based(More)
This paper investigates the creation of efficiency measurements structures of decision-making units (DMUs) called NeuroDEA, by using high-speed optimization modules called Neuro-LP, inspired in the "philosophy" of an unconventional artificial neural network (ANN) and numerical methods. In addition, the linear programming problem LPP is transformed into an(More)
In this paper we measure, with a DEA BCC model, the economic efficiency of Embrapa’s (Brazilian Agricultural Research Corporation) research centers. We model the DEA economic efficiency as a linear function of the contextual variables revenue generation capacity, partnership intensity, improvement of administrative processes, cost rationalization, size and(More)