Risk management for fuzzy random MST problem based on conditional Value-at-Risk

Takashi Hasuike, Hideki Katagiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper deals with a minimum spanning tree problem where each edge weight is a fuzzy random variable. In terms of risk management in order to avoid adverse impacts derived from uncertainty, conditional Value-at-Risk including a necessity measure for fuzziness is introduced as a risk measure. Furthermore, by performing the deterministic equivalent transformation, the proposed problem is transformed into an existing minimum spanning tree problem to apply polynomialtime algorithms, and a solution algorithm is developed to solve the proposed problem.

Original languageEnglish
Title of host publication2011 International Conference on Information Science and Applications, ICISA 2011
DOIs
Publication statusPublished - 2011 Jul 18
Externally publishedYes
Event2011 International Conference on Information Science and Applications, ICISA 2011 - Jeju Island, Korea, Republic of
Duration: 2011 Apr 262011 Apr 29

Publication series

Name2011 International Conference on Information Science and Applications, ICISA 2011

Other

Other2011 International Conference on Information Science and Applications, ICISA 2011
CountryKorea, Republic of
CityJeju Island
Period11/4/2611/4/29

Keywords

  • Conditional Value-at-Risk
  • Minimum spanning tree
  • Randomness and fuzziness
  • Risk management

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Hasuike, T., & Katagiri, H. (2011). Risk management for fuzzy random MST problem based on conditional Value-at-Risk. In 2011 International Conference on Information Science and Applications, ICISA 2011 [5772344] (2011 International Conference on Information Science and Applications, ICISA 2011). https://doi.org/10.1109/ICISA.2011.5772344