Which uncertainty is important in multistage stochastic programmes? A case from maritime transportation

Giovanni Pantuso, Kjetil Fagerholt, Stein W. Wallace

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    Given that the scope of stochastic programming is to suggest good decisions and not to estimate probability distributions, we demonstrate in this paper how to numerically evaluate which properties of random variables are more important to capture in a stochastic programming model. Such analysis, performed before data collection, can indicate which information should be primarily sought, and which is not critical for the final decision. We apply the analysis to a real-life instance of the maritime fleet renewal. Results show that some properties of the stochastic phenomena, such as the correlation between random variables, have very little influence on the final decision.
    Original languageEnglish
    JournalI M A Journal of Management Mathematics
    Volume28
    Issue number1
    Pages (from-to)5-17
    Number of pages13
    ISSN1471-678X
    DOIs
    Publication statusPublished - 2017

    Keywords

    • Fleet planning
    • Modelling uncertainty
    • Stochastic programming

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