Modeling multi-stage decision optimization problems

摘要

Multi-stage optimization under uncertainty techniques can be used to solvelong-term management problems. Although many optimization modeling languageextensions as well as computational environments have been proposed, theacceptance of this technique is generally low, due to the inherent complexityof the modeling and solution process. In this paper a simplification toannotate multi-stage decision problems under uncertainty is presented - thissimplification contrasts with the common approach to create an extension on topof an existing optimization modeling language. This leads to the definition ofmeta models, which can be instanced in various programming languages. Anexample using the statistical computing language R is shown.