|edoc-Server der Humboldt-Universität zu Berlin|
David P. Morton, The University of Texas at Austin|
Javier Salmerón, Naval Postgraduate School
R. Kevin Wood, Naval Postgraduate School
|Title:||A stochastic program for optimizing military sealift subject to attack|
|Date of Acceptance:||19.12.2002|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10058637)|
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|We describe a stochastic program for planning the wartime, sealift deployment of military cargo subject to attack. The cargo moves on ships from US or allied seaports of embarkation through seaports of debarkation (SPODs) near the theater of war where it is unloaded and sent on to final , in-theater destinations. The question we ask is: Can a deployment-planning model, with probabilistic knowledge of the time and location of potential enemy attacks on SPODs, successfully hedge against those attacks? That is, can this knowledge be used to reduce the expected disruption caused by such attacks? A specialized, multi-stage stochastic mixed-integer program is developed and answers that question in the affirmative. Furthermore, little penalty is incurred with the stochastic solution when no attack occurs, and worst-case scenarios are better. In the short term, insight gained from the stochastic-programming approach also enables better scheduling using current rule-based methods.|
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