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Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology

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Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology. / Kadziński, Miłosz; Martyn, Krzysztof; Cinelli, Marco; Słowiński, Roman; Corrente, Salvatore; Greco, Salvatore.

In: Knowledge-Based Systems, Vol. 218, 106879, 22.04.2021, p. 1-22.

Research output: Contribution to journalArticlepeer-review

Harvard

Kadziński, M, Martyn, K, Cinelli, M, Słowiński, R, Corrente, S & Greco, S 2021, 'Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology', Knowledge-Based Systems, vol. 218, 106879, pp. 1-22. https://doi.org/10.1016/j.knosys.2021.106879

APA

Kadziński, M., Martyn, K., Cinelli, M., Słowiński, R., Corrente, S., & Greco, S. (2021). Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology. Knowledge-Based Systems, 218, 1-22. [106879]. https://doi.org/10.1016/j.knosys.2021.106879

Vancouver

Author

Kadziński, Miłosz ; Martyn, Krzysztof ; Cinelli, Marco ; Słowiński, Roman ; Corrente, Salvatore ; Greco, Salvatore. / Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology. In: Knowledge-Based Systems. 2021 ; Vol. 218. pp. 1-22.

Bibtex

@article{623933ef434d4bc08c7df4a4e657c7bd,
title = "Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology",
abstract = "We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.",
keywords = "Multiple criteria sorting, Multiple decisions, Nanomaterials, Non-monotonic value functions, Precaution level, Preference disaggregation",
author = "Mi{\l}osz Kadzi{\'n}ski and Krzysztof Martyn and Marco Cinelli and Roman S{\l}owi{\'n}ski and Salvatore Corrente and Salvatore Greco",
note = "Funding Information: Mi{\l}osz Kadzi{\'n}ski acknowledges support by the research funds (SBAD in 2021) of Poznan University of Technology, Poland . Krzysztof Martyn acknowledges support from the Polish National Science Center under the SONATA BIS project (grant no. DEC-2019/34/E/HS4/00045 ). Marco Cinelli acknowledges funding from the European Union{\textquoteright}s Horizon 2020 research and innovation program under grant agreement no. 743553 . Salvatore Corrente and Salvatore Greco acknowledge the support of the Ministero dell{\textquoteright}Istruzione, dell{\textquoteright}Universit{\'a} e della Ricerca (MIUR) – PRIN 2017, project “Multiple Criteria Decision Analysis and Multiple Criteria Decision Theory”, grant 2017CY2NCA , and of the research projects “Multicriteria analysis to support sustainable decisions” and “Analysis and measurement of the competitiveness of enterprises, and territorial sectors and systems: a multicriteria approach” of the Department of Economics and Business of the University of Catania, Italy . Funding Information: Mi?osz Kadzi?ski acknowledges support by the research funds (SBAD in 2021) of Poznan University of Technology, Poland. Krzysztof Martyn acknowledges support from the Polish National Science Center under the SONATA BIS project (grant no. DEC-2019/34/E/HS4/00045). Marco Cinelli acknowledges funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 743553. Salvatore Corrente and Salvatore Greco acknowledge the support of the Ministero dell'Istruzione, dell'Universit? e della Ricerca (MIUR) ? PRIN 2017, project ?Multiple Criteria Decision Analysis and Multiple Criteria Decision Theory?, grant 2017CY2NCA, and of the research projects ?Multicriteria analysis to support sustainable decisions? and ?Analysis and measurement of the competitiveness of enterprises, and territorial sectors and systems: a multicriteria approach? of the Department of Economics and Business of the University of Catania, Italy. Publisher Copyright: {\textcopyright} 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = apr,
day = "22",
doi = "10.1016/j.knosys.2021.106879",
language = "English",
volume = "218",
pages = "1--22",
journal = "Knowledge-Based Systems",
issn = "0950-7051",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Preference disaggregation method for value-based multi-decision sorting problems with a real-world application in nanotechnology

AU - Kadziński, Miłosz

AU - Martyn, Krzysztof

AU - Cinelli, Marco

AU - Słowiński, Roman

AU - Corrente, Salvatore

AU - Greco, Salvatore

N1 - Funding Information: Miłosz Kadziński acknowledges support by the research funds (SBAD in 2021) of Poznan University of Technology, Poland . Krzysztof Martyn acknowledges support from the Polish National Science Center under the SONATA BIS project (grant no. DEC-2019/34/E/HS4/00045 ). Marco Cinelli acknowledges funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 743553 . Salvatore Corrente and Salvatore Greco acknowledge the support of the Ministero dell’Istruzione, dell’Universitá e della Ricerca (MIUR) – PRIN 2017, project “Multiple Criteria Decision Analysis and Multiple Criteria Decision Theory”, grant 2017CY2NCA , and of the research projects “Multicriteria analysis to support sustainable decisions” and “Analysis and measurement of the competitiveness of enterprises, and territorial sectors and systems: a multicriteria approach” of the Department of Economics and Business of the University of Catania, Italy . Funding Information: Mi?osz Kadzi?ski acknowledges support by the research funds (SBAD in 2021) of Poznan University of Technology, Poland. Krzysztof Martyn acknowledges support from the Polish National Science Center under the SONATA BIS project (grant no. DEC-2019/34/E/HS4/00045). Marco Cinelli acknowledges funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 743553. Salvatore Corrente and Salvatore Greco acknowledge the support of the Ministero dell'Istruzione, dell'Universit? e della Ricerca (MIUR) ? PRIN 2017, project ?Multiple Criteria Decision Analysis and Multiple Criteria Decision Theory?, grant 2017CY2NCA, and of the research projects ?Multicriteria analysis to support sustainable decisions? and ?Analysis and measurement of the competitiveness of enterprises, and territorial sectors and systems: a multicriteria approach? of the Department of Economics and Business of the University of Catania, Italy. Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/4/22

Y1 - 2021/4/22

N2 - We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.

AB - We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.

KW - Multiple criteria sorting

KW - Multiple decisions

KW - Nanomaterials

KW - Non-monotonic value functions

KW - Precaution level

KW - Preference disaggregation

UR - http://www.scopus.com/inward/record.url?scp=85101642478&partnerID=8YFLogxK

U2 - 10.1016/j.knosys.2021.106879

DO - 10.1016/j.knosys.2021.106879

M3 - Article

AN - SCOPUS:85101642478

VL - 218

SP - 1

EP - 22

JO - Knowledge-Based Systems

JF - Knowledge-Based Systems

SN - 0950-7051

M1 - 106879

ER -

ID: 26642012