Categories

jump-dev

  • JuMP-dev 2025

    JuMP-dev 2025 logo

    JuMP-dev 2025 will be held November 17–20, 2025 in Auckland, New Zealand.

    This is the week following CPAIOR 2025, which will be held November 10–13, 2025 in Melbourne, Australia. (Melbourne is a 4 hour flight and 2 hour time difference from New Zealand.)

    Outline

    The purpose of JuMP-dev is to bring...

  • JuMP-dev 2023

    JuMP-dev 2023 was held in person, 27-29 July, 2023 in Cambridge, Massachusetts. It was co-located with JuliaCon 2023.

    Photo of Speakers and Organizers (most but not all)

    Outline

    The purpose of JuMP-dev is to bring together students, researchers, and practitioners with interests in the methodological, algorithmic, and software aspects of JuMP and related packages....

  • JuMP-dev 2022

    We are pleased to announce that JuMP-dev 2022 will be co-located with JuliaCon 2022!

    This year JuliaCon is virtual, and will be held 27-29 July, 2022.

    Outline

    The purpose of JuMP-dev is to bring together students, researchers, and practitioners with interests in the methodological, algorithmic, and software aspects of JuMP and related packages. In particular, we invite...

  • JuMP-dev 2021

    We are pleased to announce that JuMP-dev 2021 will be co-located with JuliaCon 2021!

    This year JuliaCon is virtual, and will be held 28-30 July, 2021.

    Outline

    The purpose of JuMP-dev is to bring together students, researchers, and practitioners with interests in the software aspects of JuMP and related packages. In particular, we invite new contributors and...

  • Guillaume Marques | Design and features of Coluna.jl

    Guillaume Marques, a Ph.D. student at the Université de Bordeaux, gave his talk that was accepted for JuMP-dev 2020 on the design and features of the Coluna.jl package during June 2020’s JuMP monthly developer call.

    Abstract

    Coluna.jl is a branch-and-cut-and-price framework written in Julia. The user introduces...

  • Cancelled: JuMP-dev 2020

    First, we hope that everyone is safe in these uncertain times. Our first priority will always be the health and well-being of the JuMP community. Therefore, we regret to announce that we have decided to cancel JuMP-dev 2020.

    Even though there are conceivable scenarios in which travel restrictions are lifted in Europe before June 15th, we feel that there...

  • JuMP Developers Meetup/Workshop

    June 12-16, 2017, at Sloan School of Business, Massachusetts Institute of Technology.

    The workshop was sponsored by the MIT Sloan Latin America Office.

    Group Photo

    Purpose

    The workshop is designed to serve as an opportunity for developers of mathematical optimization software within the JuMP “stack” (i.e., solvers, solver interfaces, MathProgBase, JuMP, and JuMP extensions) to...


conferences


milestones

  • Celebrating the first 1000 stars on GitHub

    JuMP just received its 1000th star on GitHub! We will use this milestone to recap JuMP’s growth and other important milestones since its beginnings as an experimental project in 2012.

    While tracking the success of an open-source project is known to be a hard problem, we have a few metrics available to us. The number of citations of the two...


releases

  • JuMP 1.15.0 is released

    We are happy to announce the release of JuMP 1.15.0.

    This is a very large minor release because it adds an entirely new data structure and API path for working with nonlinear programs.

    The previous nonlinear interface remains unchanged and is documented at Nonlinear Modeling (Legacy). The new interface is a treated as a non-breaking feature addition and is...

  • JuMP 1.0.0 is released

    We are happy to announce the release of JuMP 1.0!

    Nearly 10 years in the making, the release of JuMP 1.0 represents a major milestone in the history of JuMP. It also represents a stable platform from which we can continue to build new and exciting features for a long time into the future.

    In this post we explain what...

  • JuMP 0.23 is released

    We are happy to announce the release of JuMP v0.23.

    This is an important release for two reasons.

    First, it serves as a release candidate for JuMP v1.0. Our criteria for tagging an official JuMP 1.0 release are:

    • there have been no bugs requiring a breaking change detected in JuMP v0.23 for at least one week
    • all commonly used...
  • An update on constraint programming in JuMP

    JuMP and MathOptInterface are oriented towards traditional mathematical optimization, encompassing problem classes such as mixed-integer linear programs and conic optimization. However, the MathOptInterface API is amenable to other kinds of formalism, including constraint programming.

    In contrast to linear or conic programs, constraint programs typically have no objective function, but a much wider variety of constraints that are supported. The...

  • JuMP 0.21.5 is released

    We are happy to announce the joint release of JuMP 0.21.5 and MathOptInterface 0.9.17! These releases are a mix of new features and some much needed performance optimizations. This should be a non-breaking release, please let us know if this isn’t the case by opening a GitHub issue or joining the Developer chatroom. We did have a couple...

  • JuMP 0.21 is released

    We are happy to announce the release of JuMP 0.21! Since the 0.20 release, 32 pull requests have been merged and 34 issues closed (listed here). The release is packed with new features and contains a couple of breaking changes. We’ll give only a quick summary of the changes here. See the release notes for more details. Here’s...


announcements


solvers

  • HiGHS.jl 0.1 released

    We are happy to announce the initial v0.1 release of HiGHS.jl, a wrapper for HiGHS.

    HiGHS is a new high-performance open-source linear programming solver being developed by Julian Hall and colleagues at the University of Edinburgh, Scotland.

    The GitHub README has information on how to install and use HiGHS.jl with JuMP.

    While HiGHS is ready...


tutorials

  • Finding multiple feasible solutions

    This tutorial demonstrates how to formulate and solve a combinatorial problem with multiple feasible solutions. In fact, we will see how to find all feasible solutions to our problem. We will also see how to enforce an “all-different” constraint on a set of integer variables.

    This post is in the same form as tutorials in the JuMP documentation but...


developers-call


general

  • JuMP, GAMS, and the IJKLM model

    A recent blog post by GAMS demonstrated a significant performance difference between JuMP and GAMS on a model they call IJKLM. We respond to this blog post by explaining the difference in performance and presenting an alternative JuMP implementation with asymptotically better performance. We also identify that differences in the input data format—not anything intrinsic to the respective libraries—explain...


jump-dev-prize


open-energy-modeling