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GAIA-SMAA-PROMETHEE for a hierarchy of interacting criteria

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  • Arcidiacono, Sally Giuseppe
  • Corrente, Salvatore
  • Greco, Salvatore

Abstract

In this paper, we propose an extension of the PROMETHEE methods. Despite PROMETHEE are among the most applied methods in Multiple Criteria Decision Aiding (MCDA), some drawbacks can be underlined with respect to their applicability since they do not take into account few characteristics of multicriteria decision problems that are very relevant in real world applications: (i) robustness regarding the plurality of compatible preference parameters; (ii) interaction between criteria; (iii) hierarchies of criteria. Even if different extensions of the PROMETHEE methods have taken into account all these aspects singularly, we propose to deal with all of them simultaneously presenting a new version which incorporates Robust Ordinal Regression (ROR), Stochastic Multicriteria Acceptability Analysis (SMAA), bipolar Choquet integral and Multiple Criteria Hierarchy Process (MCHP). ROR and SMAA permit to consider all the instances of the considered preference model compatible with the preference information provided by the DM; the bipolar Choquet integral is able to represent the possible positive and negative interactions between criteria as well as the antagonistic effect between some of them; finally, the MCHP permits to decompose the problem in small parts so that each of them can be analyzed more in detail with respect to the problem at hand. Moreover, we also introduce an extension of the GAIA technique to handle visualization in MCDA problems presenting interactions and antagonistic effects between criteria organized in a hierarchy. Furthermore it gives the possibility to display the plurality of instances of the preference model considered by SMAA. A didactic example will illustrate the proposed methodology.

Suggested Citation

  • Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2018. "GAIA-SMAA-PROMETHEE for a hierarchy of interacting criteria," European Journal of Operational Research, Elsevier, vol. 270(2), pages 606-624.
  • Handle: RePEc:eee:ejores:v:270:y:2018:i:2:p:606-624
    DOI: 10.1016/j.ejor.2018.03.038
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    1. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    2. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "The Ordinal Input for Cardinal Output Approach of Non-compensatory Composite Indicators: The PROMETHEE Scoring Method," MPRA Paper 95816, University Library of Munich, Germany.
    3. Panagiotis Isigonis & Salvatore Corrente & Stergios Vakalis, 2024. "A Framework for Assessing Hydrochars from Hydrothermal Carbonisation of Agrowaste with the Use of MCDA: Application with the Hierarchical SMAA-PROMETHEE Method," Sustainability, MDPI, vol. 16(1), pages 1-12, January.
    4. Gaganis, Chrysovalantis & Pasiouras, Fotios & Tasiou, Menelaos & Zopounidis, Constantin, 2021. "CISEF: A composite index of social, environmental and financial performance," European Journal of Operational Research, Elsevier, vol. 291(1), pages 394-409.
    5. García-Cáceres, Rafael Guillermo, 2020. "Stochastic Multicriteria Acceptability Analysis – Matching (SMAA-M)," Operations Research Perspectives, Elsevier, vol. 7(C).
    6. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2021. "Robust stochastic sorting with interacting criteria hierarchically structured," European Journal of Operational Research, Elsevier, vol. 292(2), pages 735-754.
    7. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2021. "The ordinal input for cardinal output approach of non-compensatory composite indicators: the PROMETHEE scoring method," European Journal of Operational Research, Elsevier, vol. 288(1), pages 225-246.
    8. Marta Bottero & Chiara D’Alpaos & Alessandra Oppio, 2019. "Ranking of Adaptive Reuse Strategies for Abandoned Industrial Heritage in Vulnerable Contexts: A Multiple Criteria Decision Aiding Approach," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    9. Chrysovalantis Gaganis & Panagiota Papadimitri & Menelaos Tasiou, 2021. "A multicriteria decision support tool for modelling bank credit ratings," Annals of Operations Research, Springer, vol. 306(1), pages 27-56, November.
    10. Puneet Agarwal & Kyle Hunt & Jun Zhuang & Bijan Sarkar & Amitrajit Sarkar & Ramesh Sharma, 2021. "An exploratory analysis for performance assessment of state police forces in india: an eclectic approach," Operational Research, Springer, vol. 21(2), pages 1125-1151, June.
    11. Pelissari, Renata & José Abackerli, Alvaro & Ben Amor, Sarah & Célia Oliveira, Maria & Infante, Kleber Manoel, 2021. "Multiple criteria hierarchy process for sorting problems under uncertainty applied to the evaluation of the operational maturity of research institutions," Omega, Elsevier, vol. 103(C).
    12. Martina Kuncova & Jana Seknickova, 2022. "Two-stage weighted PROMETHEE II with results’ visualization," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 547-571, June.
    13. Paweł Ziemba, 2021. "Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods," Energies, MDPI, vol. 14(22), pages 1-25, November.
    14. Costa, Ana Sara & Corrente, Salvatore & Greco, Salvatore & Figueira, José Rui & Borbinha, José, 2020. "A robust hierarchical nominal multicriteria classification method based on similarity and dissimilarity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 986-1001.

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