Titlebook: Algorithmic Decision Making with Python Resources; From Multicriteria P Raymond Bisdorff Textbook 2022 The Editor(s) (if applicable) and Th

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https://doi.org/10.1007/978-3-7091-9396-9 the choice of her future University studies. We present Alice’s performance tableau—potential foreign language study programs, her decision objectives, performance criteria and performance evaluations—and build a best choice recommendation for her. A thorough robustness analysis confirms a very best choice.

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Working with Bipolar-Valued Digraphsof a randomly valued digraph, we illustrate some basic digraph manipulation methods, like drawing the digraph, dividing the digraph into its asymmetric and symmetric parts, separating the border from the inner part, computing associated dual, converse and codual digraphs, and operating symmetric and

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Working with Outranking Digraphsiteria performance tableau, we construct the corresponding bipolar-valued outranking relation from pairwise comparisons. The resulting bipolar-valued outranking characteristics may be recoded. Finally, the codual outranking digraph gives us the associated strict outranking relation.

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Building a Best Choice Recommendationexplore the given performance tableau and compute the corresponding outranking digraph. After presenting the pragmatic principles that govern our best choice recommendation algorithm we solve the best office location choice problem.

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Who Wins the Election?e, we consider pairwise comparisons of election candidates and balance the number of times the first beats the second against the number of times the second beats the first. Thus we obtain the majority margins digraph, in fact a bipolar-valued digraph. When the voters express contradictory linear vo

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Rating-by-Ranking with Learned Performance Quantile Normse quantiles learned from historical performance data gathered from similar decision alternatives observed in the past. We show how to learn performance quantiles from such historical performance tableaux. New performance records may now be rated with respect to these quantile norms.

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