StAMPL: A Filtration-Oriented Modeling Tool for Stochastic Programming

Every multistage stochastic programming problem with recourse (MSPR) contains a filtration process. In this research, we created a notation that makes the filtration process the central syntactic construction of the MSPR. As a result, we achieve lower redundancy and higher modularity than is possible with the mathematical notation commonly associated with stochastic programming. To experiment with our ideas we have created StAMPL, a specialized modeling tool for the MSPR, which implements our notation and which converts models written using that syntax to instances that can be solved using standard mechanisms. Using this approach, we are able to represent models in a very clean, simple, and scalable format, while maintaining almost all the power of the AMPL modeling language.


Forthcoming in INFORMS Journal on Computing. Contact author Leo Lopes,, to request a copy in the interim.