Litcius/Paper detail

<b>CVXR</b>: An <i>R</i> Package for Disciplined Convex Optimization

Anqi Fu, Balasubramanian Narasimhan, Stephen Boyd

2020Journal of Statistical Software116 citationsDOIOpen Access PDF

Abstract

CVXR is an R package that provides an object-oriented modeling language for convex optimization, similar to CVX, CVXPY, YALMIP, and Convex.jl. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the restrictive form required by most solvers. The user specifies an objective and set of constraints by combining constants, variables, and parameters using a library of functions with known mathematical properties. CVXR then applies signed disciplined convex programming (DCP) to verify the problem's convexity. Once verified, the problem is converted into standard conic form using graph implementations and passed to a cone solver such as ECOS or SCS. We demonstrate CVXR's modeling framework with several applications.

Topics & Concepts

SolverConic optimizationConic sectionComputer scienceImplementationRegular polygonConvex optimizationSyntaxMathematical optimizationSet (abstract data type)Programming languageGraphTheoretical computer scienceConvex functionAlgorithmConvex hullSecond-order cone programmingAnswer set programmingConvex analysisSatisfiability modulo theoriesConvex setOptimization problemInteger programmingLinear programmingHypergraphAdvanced Optimization Algorithms ResearchAdvanced Multi-Objective Optimization AlgorithmsConstraint Satisfaction and Optimization
<b>CVXR</b>: An <i>R</i> Package for Disciplined Convex Optimization | Litcius