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Intuitionistic Multi-criteria Group Decision-Making for Evacuation Modelling with Storage at Nodes

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Hybrid Intelligent Systems (HIS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 647))

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Abstract

In this paper, we consider an algorithm for emergency decision-making in fuzzy intuitionistic environment. To transport the maximum number of aggrieved from the dangerous area to the safe destination, a dynamic flow model with transit arc capacities is constructed. The intermediate nodes of the network can store the flow in order for the flow to be maximized. Uncertain experts’ evaluations and high level of hesitance are incorporated into the decision-making process as fuzzy intuitionistic numbers. Multi-attribute group decision-making is used to rank the intermediate shelters to evacuate the maximum possible number of aggrieved. In the method, experts have different weights for different attributes, which allows considering the degree of experts’ competence for different attributes. The attribute weights are not known beforehand and are defined during the algorithm. A case study is conducted to illustrate evacuation of the maximum number of aggrieved with intermediate location at nodes with limited capacities in order to transport evacuees to the safe destination based on modified fuzzy intuitionistic TOPSIS.

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Acknowledgments

The research was funded by the Russian Science Foundation project No. 22–71-10121, https://rscf.ru/en/project/22-71-10121/ implemented by the Southern Federal University.

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Authors and Affiliations

  1. Southern Federal University, Taganrog, Russia

    Evgeniya Gerasimenko & Alexander Bozhenyuk

Authors
  1. Evgeniya Gerasimenko
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  2. Alexander Bozhenyuk
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Corresponding author

Correspondence to Evgeniya Gerasimenko .

Editor information

Editors and Affiliations

  1. Faculty of Computing and Data Science, FLAME University, Pune, Maharashtra, India

    Ajith Abraham

  2. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  3. Symbiosis International University, Pune, India

    Ketan Kotecha

  4. University of Jinan, Jinan, China

    Kun Ma

  5. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Mala, Kerala, India

    Pooja Manghirmalani Mishra

  6. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

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Gerasimenko, E., Bozhenyuk, A. (2023). Intuitionistic Multi-criteria Group Decision-Making for Evacuation Modelling with Storage at Nodes. In: Abraham, A., Hong, TP., Kotecha, K., Ma, K., Manghirmalani Mishra, P., Gandhi, N. (eds) Hybrid Intelligent Systems. HIS 2022. Lecture Notes in Networks and Systems, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-031-27409-1_61

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