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Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression

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  • Corrente, Salvatore
  • Greco, Salvatore
  • Ishizaka, Alessio

Abstract

We consider multiple criteria decision aiding in the case of interaction between criteria. In this case the usual weighted sum cannot be used to aggregate evaluations on different criteria and other value functions with a more complex formulation have to be considered. The Choquet integral is the most used technique and also the most widespread in the literature. However, the application of the Choquet integral presents two main problems being the necessity to determine the capacity, which is the function that assigns a weight not only to all single criteria but also to all subset of criteria, and the necessity to express on the same scale evaluations on different criteria. While with respect to the first problem we adopt the recently introduced Non-Additive Robust Ordinal Regression (NAROR) taking into account all the capacities compatible with the preference information provided by the DM, with respect to the second one we build the common scale for the considered criteria using the Analytic Hierarchy Process (AHP). We propose to use AHP on a set of reference points in the scale of each criterion and to use an interpolation to obtain the other values. This permits to reduce considerably the number of pairwise comparisons usually required by the DM when applying AHP. An illustrative example details the application of the proposed methodology.

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  • Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio, 2016. "Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression," Omega, Elsevier, vol. 61(C), pages 2-18.
  • Handle: RePEc:eee:jomega:v:61:y:2016:i:c:p:2-18
    DOI: 10.1016/j.omega.2015.07.003
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    References listed on IDEAS

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    Cited by:

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    5. Volker Kuppelwieser & Fouad Ben Abdelaziz & Olfa Meddeb, 2020. "Unstable interactions in customers’ decision making: an experimental proof," Annals of Operations Research, Springer, vol. 294(1), pages 479-499, November.
    6. Zhang, Ling & Zhang, Lei & Xu, Yan & Zhou, Peng & Yeh, Chung-Hsing, 2020. "Evaluating urban land use efficiency with interacting criteria: An empirical study of cities in Jiangsu China," Land Use Policy, Elsevier, vol. 90(C).
    7. Beliakov, Gleb, 2022. "Knapsack problems with dependencies through non-additive measures and Choquet integral," European Journal of Operational Research, Elsevier, vol. 301(1), pages 277-286.
    8. Li, Jianping & Yao, Xiaoyang & Sun, Xiaolei & Wu, Dengsheng, 2018. "Determining the fuzzy measures in multiple criteria decision aiding from the tolerance perspective," European Journal of Operational Research, Elsevier, vol. 264(2), pages 428-439.
    9. Jian-Zhang Wu & Yi-Ping Zhou & Li Huang & Jun-Jie Dong, 2019. "Multicriteria Correlation Preference Information (MCCPI)-Based Ordinary Capacity Identification Method," Mathematics, MDPI, vol. 7(3), pages 1-13, March.
    10. Silvia Angilella & Sally Giuseppe Arcidiacono & Salvatore Corrente & Salvatore Greco & Benedetto Matarazzo, 2020. "An application of the SMAA–Choquet method to evaluate the performance of sailboats in offshore regattas," Operational Research, Springer, vol. 20(2), pages 771-793, June.
    11. Miguel Ortiz-Barrios & Juan Cabarcas-Reyes & Alessio Ishizaka & Maria Barbati & Natalia Jaramillo-Rueda & Giovani Jesús Carrascal-Zambrano, 2021. "A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry," Annals of Operations Research, Springer, vol. 307(1), pages 443-481, December.
    12. Hamadneh, Jamil & Duleba, Szabolcs & Esztergár-Kiss, Domokos, 2022. "Stakeholder viewpoints analysis of the autonomous vehicle industry by using multi-actors multi-criteria analysis," Transport Policy, Elsevier, vol. 126(C), pages 65-84.
    13. Pinto, F.S. & Costa, A.S. & Figueira, J.R. & Marques, R.C., 2017. "The quality of service: An overall performance assessment for water utilities," Omega, Elsevier, vol. 69(C), pages 115-125.
    14. Guo, Mengzhuo & Liao, Xiuwu & Liu, Jiapeng & Zhang, Qingpeng, 2020. "Consumer preference analysis: A data-driven multiple criteria approach integrating online information," Omega, Elsevier, vol. 96(C).
    15. Kunsch, Pierre L. & Ishizaka, Alessio, 2018. "Multiple-criteria performance ranking based on profile distributions: An application to university research evaluations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 154(C), pages 48-64.

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