Convex.jl is a Julia package for Disciplined Convex Programming (DCP). Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl can solve: linear programs; mixed-integer linear programs and mixed-integer second-order cone programs; dcp-compliant convex programs including second-order cone programs (SOCP); exponential cone programs; semidefinite programs (SDP). Convex.jl supports many solvers, including Mosek, Gurobi, ECOS, SCS and GLPK, through the MathProgBase interface. Note that Convex.jl was previously called CVX.jl. This package is under active development; we welcome bug reports and feature requests. For usage questions, please contact us via the JuliaOpt mailing list.

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References in zbMATH (referenced in 1 article )

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  1. P. K. Mogensen; A. N. Riseth: Optim: A mathematical optimization package for Julia (2018) not zbMATH