Nossa pesquisa científica

Concentramos nossos estudos em três grandes áreas: Pesquisa Operacional, Tomada de Decisão e Inteligência Computacional.

Principais tópicos

  • tomada de decisão multicritério (individual e em grupo)
  • esquemas de consenso
  • otimização multiobjetivo
  • métodos de programação matemática
  • planejamento de experimentos, análise de sensibilidade e modelos funcionalmente orientados
  • modelagem matemática de sistemas e processos
  • consideração do fator de incerteza e sua superação
  • controle fuzzy e sistemas especialistas
  • aprendizagem estatística, redes neurais, data mining
  • identificação e análise de sistemas dinâmicos

Publicações relevantes

I. Kokshenev, R. Parreiras, P. Ya. Ekel, G. B. Alves, and S. V. Menicucci, "A Web-based Decision Support Center for Electrical Energy Companies," IEEE Transactions on Fuzzy Systems, 23 (1), pp. 16 - 28, 2014
P. Ekel, M. Junges, I. Kokshenev, and R. Parreiras, "Sensitivity and functionally oriented models for power system planning, operation, and control," International Journal of Electric Power and Energy Systems, 45 (1), pp. 2846-2868, 2013
R. Parreiras, P. Ekel, and F. Bernandes Jr., "A dynamic consensus scheme based on a nonreciprocal fuzzy preference relation modeling," Information Sciences, 211 (1), pp. 1-17, 2012
R.O. Parreiras, P.Ya. Ekel, and D.C. Morais, "Fuzzy set based consensus schemes for multicriteria group decision making applied to strategic planning," Group Decision and Negotiation, 21 (2), pp. 153-183, 2012
W. Pedrycz, P. Ekel, and R. Parreiras, Fuzzy Multicriteria Decision-Making: Models, Methods, and Applications, New York/Chichester/Brisbane, John Wiley & Sons, 2011
P. Ekel, I. Kokshenev, R. Palhares, R. Parreiras, F. Schuffner Neto, "Multicriteria analysis based on constructing payoff matrices and applying methods of decision making in fuzzy environment," Optimization and Engineering, 12 (1-2), pp. 5-29, 2011
Ye. Bodyanskiy, Ye. Gorshkov, I. Kokshenev, V. Kolodyazhniy, "Evolving Fuzzy Classification of Nonstationary Time Series," Evolving Intelligent Systems: Methodology and Applications, (Ed.: P. Angelov, D. Filev and N. Kasabov), New York, John Wiley, pp. 301-313, 2010
I. Kokshenev, A.P. Braga, "An efficient multi-objective learning algorithm for RBF neural network," Neurocomputing, 73 (16-18), pp. 2799–2808, 2010
P.Ya. Ekel and F.H. Schuffner Neto, "Algorithms of discrete optimization and their application to problems with fuzzy coefficients," Information Sciences, 176 (19), pp. 2846-2868, 2006
P.Ya. Ekel, "Fuzzy sets and models of decision making," Computers & Mathematics with Applications, 44 (7), pp. 863-875, 2002
P. Ekel, W. Pedrycz, and R. Schinzinger, "A general approach to solving a wide class of fuzzy optimization problems," Fuzzy Sets and Systems, 97 (1), pp. 49-66, 1998