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Sequential solver for nonlinear optimization

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SeqOpt.jl

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WARNING: This package is still at its early stage of development.

SeqOpt.jl is a sequential solver for nonlinear optimization. It implements a generalization of Sequential quadratic programming to nonlinear conic programs developed in:

Torbjørn Cunis & Benoît Legat. Sequential sum-of-squares programming for analysis of nonlinear systems. Submitted to the 2023 American Control Conference, arXiv:2210.02142.

License

SeqOpt.jl is licensed under the MIT License.

Installation

Install SeqOpt using Pkg.add:

import Pkg
Pkg.add("https://github.com/blegat/SeqOpt.jl")

Use with JuMP

Use SeqOpt with JuMP as follows:

using JuMP
import SCS
import SeqOpt
model = JuMP.Model(() -> SeqOpt.Optimizer(SCS.Optimizer))

Replace SCS.Optimizer with an optimizer capable of solving a linearized version of your optimization problem.

Citing

See CITATION.bib.

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Sequential solver for nonlinear optimization

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