|edoc-Server der Humboldt-Universität zu Berlin|
Andreas Märkert, University of Duisburg-Essen|
Rüdiger Schultz, University of Duisburg-Essen
|Title:||On deviation measures in stochastic integer programming|
|Date of Acceptance:||13.09.2004|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10059639)|
|Keywords (eng):||Stochastic programming, mean-risk models, mixed-integer optimization|
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
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|We propose extensions of traditional expectation-based stochastic integer programs to mean-risk models. Risk is measured by expected deviations of suitable random variables from their means or from preselected targets. We derive structural properties of the resulting stochastic programs and present first algorithmic ideas to achieve problem decomposition.|
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