Continuous reinforcement operator applied to resilience in disaster rescue networks

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Abstract

Resilience measurement can be viewed as a multicriteria hierarchical decision making problem since calculating the final level of resilience involves measuring different criteria, at several hierarchical levels, and then merging the information together. In this paper, a resilience model for disaster rescue networks is discussed with a full-reinforcement operator, denoted continuous reinforcement operator. This approach is tested with different levels of reinforcement and the results are compared with those from a Fuzzy Inference System. The proposed approach offers interesting features to support balanced development of disaster rescue networks and facilitates managerial decisions by imposing standards for criteria to penalize or reward the information fusion process.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2018-July
ISBN (Electronic)978-1-5090-6020-7
DOIs
Publication statusPublished - 12 Oct 2018
Event2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Rio de Janeiro, Brazil
Duration: 8 Jul 201813 Jul 2018

Conference

Conference2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
CountryBrazil
CityRio de Janeiro
Period8/07/1813/07/18

Keywords

  • Averaging Aggregation Operator
  • Disaster Rescue Network
  • Full-Reinforcement Aggregation Operators
  • Multiple Criteria Decision Making
  • Resilience

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  • Cite this

    Jassbi, J. J., Ribeiro, R. A., Camarinha-Matos, L. M., Barata, J., & Gomes, M. I. (2018). Continuous reinforcement operator applied to resilience in disaster rescue networks. In 2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings (Vol. 2018-July). [8491482] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2018.8491482