Dualization.jl is an extension package for MathOptInterface.jl that formulates the dual of conic optimization problems.

Dualization.jl has two main features:

• The Dualization.dualize function that computes the dual formulation of either a MathOptInterface.jl or a JuMP model.
• The Dualization.dual_optimizer function that creates a MathOptInterface-compatible optimizer that solves the dual of the problem instead of the primal.

Dualization.jl is licensed under the MIT License.

Install Dualization using Pkg.add:

import Pkg
Pkg.add("Dualization")

To compute the dual formulation of a JuMP model, use dualize:

using JuMP, Dualization
model = Model()
# ... build model ...
dual_model = dualize(model)

To solve the dual formulation of a JuMP model, create a dual_optimizer:

using JuMP, Dualization, SCS
model = Model(dual_optimizer(SCS.Optimizer))
# ... build model ...
optimize!(model)  # Solves the dual instead of the primal

The documentation for Dualization.jl includes a detailed description of the dual reformulation, along with examples and an API reference.