Dynamic-R: a “challenge-free” method for rating problem statements

Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identifie...
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Autor*in:	Raboun, Oussama [verfasserIn] Chojnacki, Eric Tsoukiàs, Alexis

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Multiple criteria decision analysis Rating problem statements Decision support systems Algorithmic decision theory

Anmerkung:	© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Annals of operations research - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984, 325(2023), 2 vom: 21. März, Seite 845-873
Übergeordnetes Werk:	volume:325 ; year:2023 ; number:2 ; day:21 ; month:03 ; pages:845-873

Links:	Volltext

DOI / URN:	10.1007/s10479-023-05276-8

Katalog-ID:	SPR051747901

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allfields	10.1007/s10479-023-05276-8 doi (DE-627)SPR051747901 (SPR)s10479-023-05276-8-e DE-627 ger DE-627 rakwb eng Raboun, Oussama verfasserin aut Dynamic-R: a “challenge-free” method for rating problem statements 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213 Chojnacki, Eric aut Tsoukiàs, Alexis (orcid)0000-0001-5772-3988 aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 325(2023), 2 vom: 21. März, Seite 845-873 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:325 year:2023 number:2 day:21 month:03 pages:845-873 https://dx.doi.org/10.1007/s10479-023-05276-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 325 2023 2 21 03 845-873
spelling	10.1007/s10479-023-05276-8 doi (DE-627)SPR051747901 (SPR)s10479-023-05276-8-e DE-627 ger DE-627 rakwb eng Raboun, Oussama verfasserin aut Dynamic-R: a “challenge-free” method for rating problem statements 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213 Chojnacki, Eric aut Tsoukiàs, Alexis (orcid)0000-0001-5772-3988 aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 325(2023), 2 vom: 21. März, Seite 845-873 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:325 year:2023 number:2 day:21 month:03 pages:845-873 https://dx.doi.org/10.1007/s10479-023-05276-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 325 2023 2 21 03 845-873
allfields_unstemmed	10.1007/s10479-023-05276-8 doi (DE-627)SPR051747901 (SPR)s10479-023-05276-8-e DE-627 ger DE-627 rakwb eng Raboun, Oussama verfasserin aut Dynamic-R: a “challenge-free” method for rating problem statements 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213 Chojnacki, Eric aut Tsoukiàs, Alexis (orcid)0000-0001-5772-3988 aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 325(2023), 2 vom: 21. März, Seite 845-873 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:325 year:2023 number:2 day:21 month:03 pages:845-873 https://dx.doi.org/10.1007/s10479-023-05276-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 325 2023 2 21 03 845-873
allfieldsGer	10.1007/s10479-023-05276-8 doi (DE-627)SPR051747901 (SPR)s10479-023-05276-8-e DE-627 ger DE-627 rakwb eng Raboun, Oussama verfasserin aut Dynamic-R: a “challenge-free” method for rating problem statements 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213 Chojnacki, Eric aut Tsoukiàs, Alexis (orcid)0000-0001-5772-3988 aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 325(2023), 2 vom: 21. März, Seite 845-873 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:325 year:2023 number:2 day:21 month:03 pages:845-873 https://dx.doi.org/10.1007/s10479-023-05276-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 325 2023 2 21 03 845-873
allfieldsSound	10.1007/s10479-023-05276-8 doi (DE-627)SPR051747901 (SPR)s10479-023-05276-8-e DE-627 ger DE-627 rakwb eng Raboun, Oussama verfasserin aut Dynamic-R: a “challenge-free” method for rating problem statements 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213 Chojnacki, Eric aut Tsoukiàs, Alexis (orcid)0000-0001-5772-3988 aut Enthalten in Annals of operations research Dordrecht [u.a.] : Springer Science + Business Media B.V, 1984 325(2023), 2 vom: 21. März, Seite 845-873 (DE-627)320615421 (DE-600)2021913-1 1572-9338 nnns volume:325 year:2023 number:2 day:21 month:03 pages:845-873 https://dx.doi.org/10.1007/s10479-023-05276-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 325 2023 2 21 03 845-873
language	English
source	Enthalten in Annals of operations research 325(2023), 2 vom: 21. März, Seite 845-873 volume:325 year:2023 number:2 day:21 month:03 pages:845-873
sourceStr	Enthalten in Annals of operations research 325(2023), 2 vom: 21. März, Seite 845-873 volume:325 year:2023 number:2 day:21 month:03 pages:845-873
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Multiple criteria decision analysis Rating problem statements Decision support systems Algorithmic decision theory
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container_title	Annals of operations research
authorswithroles_txt_mv	Raboun, Oussama @@aut@@ Chojnacki, Eric @@aut@@ Tsoukiàs, Alexis @@aut@@
publishDateDaySort_date	2023-03-21T00:00:00Z
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author	Raboun, Oussama
spellingShingle	Raboun, Oussama misc Multiple criteria decision analysis misc Rating problem statements misc Decision support systems misc Algorithmic decision theory Dynamic-R: a “challenge-free” method for rating problem statements
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topic_title	Dynamic-R: a “challenge-free” method for rating problem statements Multiple criteria decision analysis (dpeaa)DE-He213 Rating problem statements (dpeaa)DE-He213 Decision support systems (dpeaa)DE-He213 Algorithmic decision theory (dpeaa)DE-He213
topic	misc Multiple criteria decision analysis misc Rating problem statements misc Decision support systems misc Algorithmic decision theory
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title_sort	dynamic-r: a “challenge-free” method for rating problem statements
title_auth	Dynamic-R: a “challenge-free” method for rating problem statements
abstract	Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract In this paper, we are interested in decision aiding problems, aiming at rating a set of objects with respect to several dimensions, called criteria. A rating problem statement consists on partitioning a set of objects into predefined ordered equivalence classes, called categories, identified by ratings. Rating problems are widely studied in the literature, either based on the utility theory, rough sets or the majority principle. The existing methods based on the majority principle present some disadvantages potentially leading to an unconvincing rating because challenged by contradictory pairwise comparisons. In this work, we present a new method providing a “convincing” (challenge-free) rating over a set of studied objects, based on the aggregation of positive and negative reasons, respectively supporting and opposing a rating. The method exploits comparisons among the objects and the profiles characterizing the categories as well as comparisons among the objects. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	Dynamic-R: a “challenge-free” method for rating problem statements
url	https://dx.doi.org/10.1007/s10479-023-05276-8
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author2	Chojnacki, Eric Tsoukiàs, Alexis
author2Str	Chojnacki, Eric Tsoukiàs, Alexis
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doi_str	10.1007/s10479-023-05276-8
up_date	2024-07-03T23:34:55.667Z
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