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The importance of stochastics in logistics modeling

Abstract

Most decisions are made under some uncertainty about hte future. Most models do not take that explicitly into account. Is that a minor issue or a major problem? Is it wise to postpone the treatment of uncertainty to real-time operations, or is it crucial to handle uncertainty already when planning operations? The purpose of this lecture is to illustrate how deterministic models, even combined with sensitivity analysis, what-if-sessions or other similar tools, can lead to rather bad decisions. We focus on a case from less-than-truckload trucking, and show model in systematic and recognizable ways. We also show how to use these systematic differences to find good solutions to stochastic optimization problems without actually solving such problems.

Category

Other

Language

English

Author(s)

  • Michal Kaut
  • Arnt-Gunnar Lium
  • Teodor Gabriel Crainic
  • Stein W. Wallace

Affiliation

  • Molde University College - Specialized University in Logistics
  • Unknown
  • SINTEF Digital
  • Canada
  • University of Montreal

Year

2007

Publisher

Hong Kong Society of Transportation Studies

Book

The trade-off between product variety and uncertainty in the textile apparel industry - the aspect of hedging

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