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

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.

Category

Academic article

Language

English

Author(s)

Affiliation

  • Norwegian University of Science and Technology
  • Technical University of Denmark
  • SINTEF Ocean / Energi og transport
  • Norwegian School of Economics

Date

11.01.2015

Year

2015

Published in

IMA Journal of Management Mathematics

ISSN

1471-678X

Publisher

Oxford University Press

Volume

28

Issue

1

Page(s)

5 - 17

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