Value of information and solution under VaR criterion for fuzzy random optimization problems

Shuming Wang, Junzo Watada

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

    1 Citation (Scopus)

    Abstract

    Under the Value-at-Risk (VaR) criterion, this paper studies on the value of information and solution for two stage fuzzy random optimization problems. First, the value of perfect information (VPI) in VaR criterion is discussed by studying the difference of the wait-and-see (WS) solution and the here-and-now (HN) solution to the two-stage fuzzy random programming with VaR criterion. Then, the value of fuzzy random solution n (VFRS) in VaR is examined by investigating the difference of the HN solution and the random solution (RS), as well as the difference of HN solution and the expected value (EV) solution. Finally, a lower bound and an upper bound for the HN solution are derived.

    Original languageEnglish
    Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
    DOIs
    Publication statusPublished - 2010
    Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona
    Duration: 2010 Jul 182010 Jul 23

    Other

    Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010
    CityBarcelona
    Period10/7/1810/7/23

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computational Theory and Mathematics

    Cite this

    Wang, S., & Watada, J. (2010). Value of information and solution under VaR criterion for fuzzy random optimization problems. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 [5584608] https://doi.org/10.1109/FUZZY.2010.5584608