Invited Session Mon.2.H 1058

Monday, 13:15 - 14:45 h, Room: H 1058

Cluster 10: Implementations & software [...]

Optimization tools for R


Chair: Erling Dalgaard Andersen



Monday, 13:15 - 13:40 h, Room: H 1058, Talk 1

Henrik A. Friberg
The R-to-MOSEK optimization interface


The Rmosek package enables the solution of large-scale optimization problems from within the R environment. Linear, quadratic and second-order cone optimization with/without integer variables are fully supported via an intuitive, and yet effective, interface to the optimizers of MOSEK. This talk will introduce the package and show it modeling and optimization abilities.



Monday, 13:45 - 14:10 h, Room: H 1058, Talk 2

Stefan Theu├čl
ROI - R Optimization Infrastructure package

Coauthors: Kurt Hornik, David Meyer


Currently, R and a wide variety of contributed
packages on CRAN as well as other package repositories offer tools to
solve many different optimization problems (see the overview at However, the user interfaces to
available optimizers and the output, i.e., the format of the
returned solution, often differ considerably. It is not only the users
interested in R as an optimization tool, but also the
developers who need to handle different optimization problem classes
transparently and who are facing this lack of
standardization. Therefore, an integrative multi-purpose optimization
framework for R seems to be desirable.
In this talk we present the R Optimization Infrastructure
package ROI, an extensible framework
for modeling and solving linear as well as nonlinear (possibly
mixed-integer) optimization problems. Without the need to learn a
domain specific language ROI enables users to employ both, open
source and commercial solvers directly within R via
so-called plugin packages.



Monday, 14:15 - 14:40 h, Room: H 1058, Talk 3

Steven Paul Dirkse
GDXRRW: Exchanging data between GAMS and R

Coauthors: Michael C. Ferris, Renger van Nieuwkoop


We discuss GDXRRW (GDX-R Read/Write), a tool for moving data between GAMS and R. This data exchange is beneficial for those in both user communities. For example, it gives R users the capability to use the superior modeling and optimization capabilities of GAMS, and it allows for visualization and analysis of GAMS data (both pre- and post-solution) directly within R to take advantage of R's wide range of functionality. The freely available tool is based on GDX (GAMS Data eXchange), a well-established and public API for sharing data.


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