David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
The aim of this article is to propose a general approach to link a stochastic programming enabler to a mathematical programming modeling language. Modelers often choose to formulate their problems in well-tested, general purpose modeling languages such as GAMS and AMPL, but these modeling languages do not currently implement a natural syntax for stochastic programming. Specialized stochastic programming tools are available to efficiently generate and solve large-scale stochastic programs, but they lack many of the convenient features of the modeling languages. The lack of a well developed link between these tools and modeling languages prevents many modelers from accessing a powerful and convenient technique to take into account uncertainties. As an attempt to fill this gap, we will present SISP (Simplified Interface for Stochastic Programming), an interface between Algebraic Modeling Languages and specialized Stochastic Programming solvers, also known as SP solvers.
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Harpreet S. Sawhney
IS&T/SPIE Electronic Imaging 1994
Richard M. Karp, Raymond E. Miller
Journal of Computer and System Sciences
Minghong Fang, Zifan Zhang, et al.
CCS 2024