Statistical and Constraint Programming Approaches for Parameter Elicitation in Lexicographic Ordering

  • Noureddine Aribi
  • Yahia Lebbah
Part of the Studies in Computational Intelligence book series (SCI, volume 488)


In this paper, we propose statistical and constraint programming approaches in order to tackle the parameter elicitation problem for the lexicographic ordering (LO) method. Like all multicriteria optimization methods, the LO method have a parameter that should be fixed carefully, either to determine the optimal solution (best tradeoff), or to rank the set of feasible solutions (alternatives). Unfortunately, the criteria usually conflict with each other, and thus, it is unlikely to find a convenient parameter for which the obtained solution will perform best for all criteria. This is why elicitation methods have been populated in order to assist the Decision Maker (DM) in the hard task of fixing the parameters. Our proposed approaches require some prior knowledge that the DM can give straightforwardly. These informations are used in order to get automatically the appropriate parameters. We also present a relevant numerical experimentations, showing the effectiveness of our approaches in solving the elicitation problem.


Parameter Elicitation Multicriteria Optimisation Constraint Programming Statistics Lexicographic ordering 


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© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.Laboratoire LITIOUniversité d’OranEl-M’NaouerAlgérie
  2. 2.Laboratoire I3S/CNRSUniversité de NiceSophia AntipolisFrance

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