Fuzzy random shortest path problem using conditional Value at Risk

Takashi Hasuike

doi:10.1109/ICSSE.2010.5551772

Fuzzy random shortest path problem using conditional Value at Risk

Takashi Hasuike^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2010 International Conference on System Science and Engineering, ICSSE 2010
Pages	439-444
Number of pages	6
DOIs	https://doi.org/10.1109/ICSSE.2010.5551772
Publication status	Published - 2010 Oct 11
Externally published	Yes
Event	2010 International Conference on System Science and Engineering, ICSSE 2010 - Taipei, Taiwan, Province of China Duration: 2010 Jul 1 → 2010 Jul 3

Publication series

Name	2010 International Conference on System Science and Engineering, ICSSE 2010

Other

Other	2010 International Conference on System Science and Engineering, ICSSE 2010
Country/Territory	Taiwan, Province of China
City	Taipei
Period	10/7/1 → 10/7/3

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

Access to Document

10.1109/ICSSE.2010.5551772

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., 5551772, 2010 International Conference on System Science and Engineering, ICSSE 2010, pp. 439-444, 2010 International Conference on System Science and Engineering, ICSSE 2010, Taipei, Taiwan, Province of China, 10/7/1. https://doi.org/10.1109/ICSSE.2010.5551772

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AB - 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.

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Fuzzy random shortest path problem using conditional Value at Risk

Abstract

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Keywords

ASJC Scopus subject areas

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