ABSTRACT Composition of probabilistic preferences is applied here together with life cycle assessment in the evaluation of sewage sludge treatment scenarios. The computations are based on the transformation of preferences for the alternatives elicited applying each criterion into probabilities of being the best. Different forms of probabilistic composition are applied and the possibility of interaction between factors is considered. The results are compared to results previously obtained with different forms of composition modeling the interaction or assuming linearity. Eight scenarios combining different processing techniques and leading to distinct end-uses are compared. These scenarios are ranked combining probabilities of preference according to five environmental impact factors: water use, energy consumption, carbon footprint, human toxicity potential and terrestrial ecotoxicity potential. In the large spectrum of views that the probabilistic approach provides, evidence is found favoring a system that includes recovery of energy to be used in a dryer and in a cement kiln.

ABSTRACT This study associates graph theory and a multi-criteria decision aid technique, presenting a different process for doing the investigation of criminal networks. In the criminal subject, privacy concerns limit identification. For this reason, the database composed of 110 actors, involving criminals and peripheral characters to the network, was identified by numbers, without names and penalties. The discrimination of critical actors in criminal networks can help law enforcement officers to conduct a more detailed investigation for their disruption. Communication between drug traffickers was transformed into different centrality indices for each actor in their social network. Centralities and actors compose a decision matrix, analyzed by the Composition of Probabilistic Preferences to identify the most relevant actors in the criminal network. Results indicated that the five actors highlighted in the real investigation have a clear distinction of importance in the network, which in a way have been ratified.

RESUMO Esta pesquisa teve como objetivo auxiliar gestores e comissões técnicas na escolha de goleiros do futebol profissional. Foi estudada uma amostra de 64 goleiros que atuam na Argentina e no Brasil. Foram analisados seus desempenhos em jogos de duas temporadas, considerando três critérios: gols sofridos por minutos jogados, percentual de gols evitados e percentual de partidas sem sofrer gols. A Composição Probabilística de Preferências foi o método escolhido para a modelagem, por considerar a variabilidade aleatória dos dados do problema e do futebol, considerado um dos esportes mais imprevisíveis. A aplicação comparou a escolha baseada na análise dos dados com as últimas convocações de goleiros para as seleções desses países. Os goleiros selecionados corresponderam aos de melhor desempenho individual, confirmando o modelo.

ABSTRACT This research aims to assist managers and technical commissions to choose professional soccer goalkeepers. A sample of 64 goalkeepers playing in Argentina and Brazil was studied. Their performance in the matches of two seasons were analyzed considering three criteria: goals against per minute played, percentage of goals and percentage of matches without conceded goals. The Composition of Probabilistic Preferences (CPP) was the method chosen for modeling, considering the random variability in the problem data and in football, considered one of the most unpredictable sports. CPP allowed to compare the choice based on the data analysis to the latest goalkeeper call-ups for these countries’ national teams. The selected goalkeepers corresponded to those presenting the best individual performance, which confirms the model.

RESUMEN Esta investigación tuvo como objetivo ayudar a gerentes y comisiones técnicas para elegir a los porteros de fútbol profesional. Una muestra de 64 porteros de Argentina y Brasil fue estudiada. Las actuaciones en los partidos de dos temporadas fueran analizadas, considerando tres criterios: goles concedidos por minutos jugados, porcentaje de goles evitados y porcentaje de partidos en los que al portero no le encajaron goles. La Composición Probabilística de Preferencias fue el método elegido, considerando la variabilidad aleatoria de los datos del problema y del fútbol, considerado uno de los deportes más impredecibles. La aplicación comparó la muestra con las últimas convocatorias de porteros de las selecciones nacionales de estos países. Los porteros seleccionados correspondieron a los de mejor rendimiento individual, confirmando el modelo.

ABSTRACT The influence of a principle of preference concentration in the process of decision making in different contexts is discussed here. A procedure exploring the concentration of preferences to derive probabilities and another to derive, with higher generality, Choquet capacities are presented. An important feature of this last procedure is that it derives capacities in a space of criteria only from matrices of probabilities of preference according to each criterion, precluding the effort of directly trying to measure the interactions between them.

Resumo Este artigo teve por objetivo apresentar uma abordagem empírica ao método de Composição Probabilística de Preferências (CPP). O método CPP se destina a escolha, ordenação e classificação de alternativas em problemas multicritério. O CPP tem explorado ampla variedade de aplicações a partir de distribuições de probabilidades contínuas. Entretanto, o uso de probabilidades empíricas, sem a necessidade de conhecer ou assumir uma função de probabilidade conjunta que origina as preferências, pode contribuir para lidar com determinados tipos de problema com escalas ordinais de preferência. A abordagem empírica é aqui aplicada em três casos, com a finalidade de ilustrar suas principais características e limitações. A proposta se mostrou satisfatória para o tratamento de preferências de avaliadores, especialmente quando o número de alternativas é reduzido em relação às opções da escala de pontos de avaliação e ao número de avaliadores, por contribuir para elevar a capacidade discriminatória dos resultados.

Abstract This paper aimed at presenting an Empirical Approach to the Composition of Probabilistic Preferences (CPP) method. The CPP method is used to choose, sort and classify alternatives in multi-criteria problems. The CPP has explored a wide variety of applications from continuous probability distributions. However, the use of empirical probabilities, without the need to know or assume a joint probability function that gives rise to preferences, can help to deal with certain types of problems with ordinal preference scales. The empirical approach is applied here in three cases, with the purpose of illustrating its main characteristics and limitations. The proposal proved to be satisfactory for treating appraisers' preferences, especially when the number of alternatives is reduced in relation to the options of the scale of assessment points and the number of appraisers, as they contribute to increase the discriminatory capacity of the results.

ABSTRACT The Composition of Probabilistic Preferences is here applied to combine eight indicators of human development. The four components of HDI are considered together with indices of inequality in longevity, schooling, and income, and the UNDP Gender Development Index. To compose the probabilities of preference by the different criteria, a pessimistic and conservative point of view is taken. This point of view, while generating the global score, results in employing for each option the probability of not presenting the lowest evaluation according to any criterion, increasing the importance assigned in the computations to the proximity to the frontier of worst performances. Alternative rankings of the 188 countries ranked in the 2015 and the 2016 Human Development Report are obtained. Capacities allowing for interactions between up to eight components are employed. Representative profiles of ordered classes are derived from the rankings. Classifications of the countries into previously determined classes are also performed.

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.

ABSTRACT How to measure the perceived influence of a course on its alumni skills? This paper describes the use of CPP-TRI as a tool to face this problem. The method was applied here in the context of a M.Sc. course evaluation. Levels of impact and importance previously determined for different features provide the framework for the analysis. Classifications by different groups of evaluators are combined. Taking into account the subjectivity in the assessments, CPP-TRI treats them as realizations of random variables. The combination of the evaluations is performed by computing joint probabilities, what avoids the assignment of weights to evaluators. Interval classifications between a hostile and a benevolent limit are provided offerings the educational evaluator a deeper understanding of the results. An additional study is here performed on the classification of the features. A total of sixteen features are sorted.