We present MultiObjectiveAlgorithms.jl, an open-source Julia library for solving multi-objective optimization problems written in JuMP. MultiObjectiveAlgorithms.jl implements a number of different solution algorithms, which all rely on an iterative scalarization of the problem from a multi-objective optimization problem to a sequence of single-objective subproblems. As part of this work, we extended JuMP to support vector-valued objective functions. Because it is based on JuMP, MultiObjectiveAlgorithms.jl can use a wide variety of commercial and open-source solvers to solve the single-objective subproblems, and it supports problem classes ranging from linear, to conic, semi-definite, and general nonlinear. MultiObjectiveAlgorithms.jl is available at https://github.com/jump-dev/MultiObjectiveAlgorithms.jl under a MPL-2 license.
Cite
@article{arxiv.2507.05501,
title = {MultiObjectiveAlgorithms.jl: a Julia package for solving multi-objective optimization problems},
author = {Oscar Dowson and Xavier Gandibleux and Gökhan Kof},
journal= {arXiv preprint arXiv:2507.05501},
year = {2026}
}