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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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發(fā)表于 2025-3-21 16:55:38 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Algorithmic Decision Making with Python Resources
期刊簡(jiǎn)稱From Multicriteria P
影響因子2023Raymond Bisdorff
視頻videohttp://file.papertrans.cn/153/152917/152917.mp4
發(fā)行地址Provides first hand step-by-step tutorials for solving didactical and practical decision problems with multiple criteria.Introduces main objects available in the Digraph3 collection of Python3 modules
學(xué)科分類International Series in Operations Research & Management Science
圖書封面Titlebook: Algorithmic Decision Making with Python Resources; From Multicriteria P Raymond Bisdorff Textbook 2022 The Editor(s) (if applicable) and Th
影響因子.This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach. These computing resources, made available under the name Digraph3, are useful in the field of Algorithmic Decision Theory and more specifically in outranking-based Multiple-Criteria Decision Aiding (MCDA)...The first part of the book presents a set of tutorials introducing the Digraph3 collection of Python3 modules and its main objects, such as bipolar-valued digraphs and outranking digraphs. In eight methodological chapters, the second part illustrates multiple-criteria evaluation models?and decision algorithms. These chapters are largely problem-oriented and demonstrate how to edit a new multiple-criteria performance tableau, how to build a best choice recommendation, how to compute the winner of an election and how to make rankings or ratings using incommensurable criteria. ..The book’s third part presents three real-world decision case studies, while the fourth part addresses more advanced topics, such as computing ordinal correlations between bipolar-valued outranking digraphs, computing kernels in bipolar-valued digraphs, testi
Pindex Textbook 2022
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發(fā)表于 2025-3-21 22:00:49 | 只看該作者
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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How to Create a New Multiple-Criteria Performance Tableau six performance criteria. We discuss in detail editing the decision alternatives, the decision objectives, the family of performance criteria, and finally, the evaluations of the decision alternatives on the performance criteria.
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HPC Ranking of Big Performance Tableauxs or millions of records. To effectively compute rankings from performance tableaux of these sizes, we propose in this chapter a collection of C-compiled and optimised . modules that may be run on HPC equipment as available, for instance, at the University of Luxembourg.
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