ROI: An Extensible R Optimization Infrastructure
Dublin Core
Title
ROI: An Extensible R Optimization Infrastructure
Subject
optimization, mathematical programming, linear programming, quadratic programming, convex programming, nonlinear programming, mixed integer programming, R.
Description
Optimization plays an important role in many methods routinely used in statistics,
machine learning and data science. Often, implementations of these methods rely on
highly specialized optimization algorithms, designed to be only applicable within a specific application. However, in many instances recent advances, in particular in the field of
convex optimization, make it possible to conveniently and straightforwardly use modern
solvers instead with the advantage of enabling broader usage scenarios and thus promoting
reusability. This paper introduces the R optimization infrastructure ROI which provides
an extensible infrastructure to model linear, quadratic, conic and general nonlinear optimization problems in a consistent way. Furthermore, the infrastructure administers many
different solvers, reformulations, problem collections and functions to read and write optimization problems in various formats
machine learning and data science. Often, implementations of these methods rely on
highly specialized optimization algorithms, designed to be only applicable within a specific application. However, in many instances recent advances, in particular in the field of
convex optimization, make it possible to conveniently and straightforwardly use modern
solvers instead with the advantage of enabling broader usage scenarios and thus promoting
reusability. This paper introduces the R optimization infrastructure ROI which provides
an extensible infrastructure to model linear, quadratic, conic and general nonlinear optimization problems in a consistent way. Furthermore, the infrastructure administers many
different solvers, reformulations, problem collections and functions to read and write optimization problems in various formats
Creator
Stefan Theußl
Source
https://www.jstatsoft.org/article/view/v094i15
Publisher
Raiffeisen Bank
International AG
International AG
Date
June 2020
Contributor
Fajar Bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Stefan Theußl
, “ROI: An Extensible R Optimization Infrastructure,” Repository Horizon University Indonesia, accessed May 11, 2025, https://repository.horizon.ac.id/items/show/8148.