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arXiv:1508.01982math.OC

JuMP: A Modeling Language for Mathematical Optimization

Iain Dunning, Joey Huchette, Miles Lubin

Abstract

JuMP is an open-source modeling language that allows users to express a wide range of optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and nonlinear) in a high-level, algebraic syntax. JuMP takes advantage of advanced features of the Julia programming language to offer unique functionality while achieving performance on par with commercial modeling tools for standard tasks. In this work we will provide benchmarks, present the novel aspects of the implementation, and discuss how JuMP can be extended to new problem classes and composed with state-of-the-art tools for visualization and interactivity.

arXiv comments
Journal reference
DOI
doi:10.1137/15M1020575
Subjects
math.OCOptimization and Control cs.MSMathematical Software

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Linked by 2 identifiable commenters in 2 comments across 2 threads, from Oct 2015 to Oct 2017.

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Discussed in comments2 threads

  1. Some Insights from a Julia Developer 1 comment

    • The JuMP paper [1] compares JuMP with all the major commercial and open source options in this area, including Pyomo. Pyomo is orders of magnitude slower than JuMP and doesn't scale as well so the comparison gets worse as problems get larger. (Pyomo had the worst performance of…

      StefanKarpinskiView on HNParent context

  2. Linear Programming in Python with CVXOPT 1 comment

    • If you're interested in model generation time, have a look at JuMP (https://github.com/JuliaOpt/JuMP.jl). More discussions on the speed of modeling languages at http://arxiv.org/abs/1312.1431 and http://arxiv.org/abs/1508.01982

      mlubinView on HNParent context

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