Fuzzy random shortest path problem using conditional Value at Risk

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

Abstract

This paper considers a fuzzy random shortest path problem and proposes a new risk measure to synthesize both stochastic conditional Value at Risk and credibility measure for fuzziness. The proposed model defined by the hybrid conditional Value at Risk is equivalently transformed into a 0-1 mixed integer programming problem. In order to this problem analytically and efficiently, the Lagrange 0-1 relaxation problem using the property of totally unimodular and proposed the efficient solution algorithm based on the hybrid algorithm of standard Dijkstra algorithm and subgradient method.

Original languageEnglish
Title of host publication2010 International Conference on System Science and Engineering, ICSSE 2010
Pages439-444
Number of pages6
DOIs
Publication statusPublished - 2010 Oct 11
Event2010 International Conference on System Science and Engineering, ICSSE 2010 - Taipei, Taiwan, Province of China
Duration: 2010 Jul 12010 Jul 3

Publication series

Name2010 International Conference on System Science and Engineering, ICSSE 2010

Other

Other2010 International Conference on System Science and Engineering, ICSSE 2010
CountryTaiwan, Province of China
CityTaipei
Period10/7/110/7/3

Keywords

  • Deterministic equivalent transformation
  • Fuzzy random variable
  • Hybrid conditional value at risk
  • Shortest path problem

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering

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  • Cite this

    Hasuike, T. (2010). Fuzzy random shortest path problem using conditional Value at Risk. In 2010 International Conference on System Science and Engineering, ICSSE 2010 (pp. 439-444). [5551772] (2010 International Conference on System Science and Engineering, ICSSE 2010). https://doi.org/10.1109/ICSSE.2010.5551772