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
Externally publishedYes
Event2011 International Conference on Information Science and Applications, ICISA 2011 - Jeju Island, Korea, Republic of
Duration: 2011 Apr 262011 Apr 29

Other

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

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Keywords

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

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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] https://doi.org/10.1109/ICISA.2011.5772344