JuMP is a modeling interface and a collection of supporting packages for mathematical optimization that is embedded in Julia. With JuMP, users formulate various classes of optimization problems with easy-to-read code, and then solve these problems using state-of-the-art open-source and commercial solvers. JuMP also makes advanced optimization techniques easily accessible from a high-level language.

JuMP will be participating as a sub-organization in NumFOCUS's application for Google Summer of Code 2021. For more information about this application see:

• NumFOCUS's main GSoC page

• Oscar Dowson

If you have an idea for GSOC2021, please make a pull request to edit this page.

A key limitation of the current version of JuMP and MathOptInterface is that they are limited to problems with a single scalar objective function. The goal of this project is to relax this requirement so that users can model and solve multi-objective optimization problems.

Technical details available in this issue

• Knowledge of JuMP and MathOptInterface
• Knowledge of multi-objective optimization

Initial steps

• Read Issue 2099
• Become familiar with previous attempts at vector-valued objectives in JuMP https://github.com/anriseth/MultiJuMP.jl

Key deliverables

• Add tests, documentation, and features for vector-valued objective problems to MathOptInterface.
  • Here was the start of a previous attempt: jump-dev/MathOptInterface.jl#968.
  • Also a reader for the MOP file format: odow/MathOptFormat.jl#95
• Revive this solver for proof-of-concept: https://github.com/odow/MOO.jl.
  • Add more tests, documentation, and features.
  • Add other multi-objective algorithms

Stretch goal

• Extend JuMP's @objective macro to work with vector-valued functions.
• Add support for vOptSolver