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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...

Mathieu Tanneau | Design and implementation of the interior-point solver Tulip

Mathieu Tanneau, a Ph.D. student at Polytechnique Montréal, gave his talk that was accepted for JuMP-dev 2020 on the design and implementation of the interior-point solver Tulip.jl during August 2020’s JuMP monthly developer call.

The talk material is available on his Github.

Abstract

Tulip.jl is...

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-dev 2020

JuMP-dev 2020 cancelled.

June 15-17, 2020, Louvain-la-Neuve, Belgium.

This workshop is the fourth JuMP-dev workshop after the first, second, and third JuMP-dev workshops.

The purpose of the workshop is to bring together students, researchers, and practitioners with interests in the software aspects of JuMP and related packages. The workshop is open for anybody to...

JuMP-dev 2020: Save the date!

We are pleased to announce that the 4th annual JuMP-dev workshop will be held June 15-17 2020 in Louvain-la-Neuve, Belgium, in conjunction with UCLouvain.

Further details, including a call for speakers, will be announced shortly.

For information on the previous JuMP-dev workshops, see: 2019, 2018, 2017.

The Third Annual JuMP-dev Workshop

March 12-14, 2019, Santiago, Chile.

Spanish version

This workshop is the third JuMP-dev workshop after the first and second JuMP-dev workshops.

GSoC News: JuMP will be participating in the 2019 Google Summer of Code under the NumFOCUS umbrella. For more information see JuMP’s project ideas...

The Second Annual JuMP-dev Workshop

June 27-29, 2018, at the Institut de Mathématiques de Bordeaux, University of Bordeaux.

The workshop was sponsored by the MIT Sloan school of management, IDEX Bordeaux, and Changhyun Kwon.

Purpose

This workshop is a follow-up to the first annual JuMP-dev workshop held in June 2017 at MIT. The purpose of...

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.

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...

JuMP talks at the 2019 INFORMS Annual Meeting

Following is a list of some JuMP related sessions and talks at the 2019 INFORMS Annual Meeting:

• Dedicated JuMP sessions:
  • SB33. JuMP for Stochastic Optimization, CC- Room 602, October 20, 2019, 11:00 AM:
    • 1 - Recent Developments in SDDP.jl.
    • 2 - Solving Multistage Stochastic Optimization Problems using JuMP.
    • 3 - Large Scale...

JuMP talks at ROADEF 2018

Following is a list of some JuMP related sessions and talks at ROADEF 2018:

• Dedicated JuMP session:
  • Julia et JuMP en recherche opérationnelle, Salle Colbert 1, February 21, 2018
    • 1 - StochDynamicProgramming.jl a Julia library for multistage stochastic optimization
    • 2 - Retour d’expérience sur Julia pour la recherche et l’enseignement en recherche opérationnelle
    ...

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...

JuMP 1.0.0 is released

Authors: Miles Lubin, Oscar Dowson, Iain Dunning, Joaquim Dias Garcia, Joey Huchette, and Benoît Legat.

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...

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

Author: Thibaut Cuvelier (@dourouc05)

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 constrast to linear or conic programs, constraint programs typically have no objective function, but a much wider variety of constraints...

JuMP 0.21.7 is released

We are happy to announce the release of JuMP 0.21.7. 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.

A key feature of interest is that we have continued to significantly revise our documentation. The Nonlinear Modeling section is now much...

JuMP 0.21.6 is released

We are happy to announce the release of JuMP 0.21.6. 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.

A key feature of interest is that we have significantly revised our documentation, including examples that are now built in the documentation....

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 Gitter chat. 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...

RelationalAI sponsors constraint programming support in JuMP

The JuMP Steering Committee is pleased to announce that we, through NumFOCUS, have signed an agreement with RelationalAI to improve constraint programming support in JuMP.

Constraint programming is a goal of the post-1.0 JuMP roadmap, and we gave an update on our progress last year.

The three main goals of this new work are to...

NumFOCUS small development grant: adding complex number support to JuMP

The JuMP Steering Committee is pleased to announce that we have received a small development grant from NumFOCUS to add complex number support to JuMP.

Currently, JuMP and MathOptInterface are limited to formulating optimization problems with real-valued decision variables. However, complex numbers appear in a variety of industrial optimization problems. One of the most important of these...

NumFOCUS signs agreement with LANL to improve nonlinear support in JuMP

The JuMP Steering Committee is pleased to announce that we, through NumFOCUS, have signed an agreement with Los Alamos National Laboratory (LANL) to improve nonlinear support in JuMP.

The agreement runs until September 2023.

At a high-level, the agreement seeks to improve nonlinear support in JuMP on two key fronts:

• improving the automatic differentiation performance in...

NumFOCUS signs agreement with MIT to provide ongoing maintenance and support

The JuMP Steering Committee is pleased to announce that we, through NumFOCUS, have signed an agreement with MIT to provide ongoing maintenance and support of JuMP as part of the National Science Foundation award OAC1835443. The agreement may be renewed on an annual basis through December 2023.

At a high-level, the agreement covers work that is...

Formalizing a governance structure

Recently, JuMP turned eight years old. (The first commit for “Julp” was made on 10 October 2012!) It has come a long way since it’s creation as a side-project of two graduate students at MIT, and as we approach a 1.0 release, we thought it was time to formalize our governance structure.

You can find the resulting document under...

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...

Finding multiple feasible solutions

Author: James Foster (@jd-foster)

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 nonlinear developers call: The JuliaSmoothOptimizers ecosystem

In February’s edition of the JuMP nonlinear developers call, Tangi Migot and Alexis Amontoison discussed the JuliaSmoothOptimizers ecosystem.

The notebooks and project files used in the talk are available as a downloadable .zip file.

Abstract

In this talk, we will give an overview...