A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding
作者： Mohammad Ghaderi , Francisco Ruiz , Núria Agell , None
DOI: 10.1016/J.EJOR.2016.11.038
关键词:
摘要: Abstract A new framework for preference disaggregation in multiple criteria decision aiding is introduced. The proposed approach aims to infer non-monotonic additive models from a set of indirect pairwise comparisons. model presented as marginal value functions and the discriminatory power inferred maximized against its complexity. To function that compatible with supplied information, methodology leads linear programming optimization problem easy solve. applicability effectiveness demonstrated thorough experimental analysis covering broad range problems.
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