Convex.jl - Convex Optimization in Julia¶
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.
In Depth Documentation:¶
- Quick Tutorial
- Basic Types
- Supported Operations
- Complex-domain Optimization
- Optimizing in a Loop