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Algorithmic Decision Making with Python Resources - From Multicriteria Performance Records to Decision Algorithms via Bipolar-Valued Outranking Digraphs (1st ed. 2022)
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Algorithmic Decision Making with Python Resources - From Multicriteria Performance Records to Decision Algorithms via Bipolar-Valued Outranking Digraphs (1st ed. 2022)
Series: International Series in Operations Research & Management Science, 324
Expected to ship within 9 - 17 working days
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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, testing for confidence or stability of
outranking statements when facing uncertain or solely ordinal
criteria significance weights, and tempering plurality tyranny
effects in social choice problems. The fifth and last part is more
specifically focused on working with undirected graphs, tree graphs
and forests. The closing chapter explores comparability, split,
interval and permutation graphs. The book is primarily intended for
graduate students in management sciences, computational statistics
and operations research. The chapters presenting algorithms for
ranking multicriteria performance records will be of computational
interest for designers of web recommender systems. Similarly, the
relative and absolute quantile-rating algorithms, discussed and
illustrated in several chapters, will be of practical interest to
public and private performance auditors. Â
General
| Imprint: |
Springer Nature Switzerland AG
|
| Country of origin: |
Switzerland |
| Series: |
International Series in Operations Research & Management Science, 324 |
| Release date: |
March 2023 |
| First published: |
2022 |
| Authors: |
Raymond Bisdorff
|
| Dimensions: |
235 x 155mm (L x W) |
| Pages: |
346 |
| Edition: |
1st ed. 2022 |
| ISBN-13: |
978-3-03-090930-7 |
| Categories: |
Books
Promotions
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| LSN: |
3-03-090930-1 |
| Barcode: |
9783030909307 |
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