JuMP: A Modeling Language for Mathematical Optimization

3/23/2017 | 4:15pm | E51-325
Reception to follow.





Miles Lubin and Joseph Huchette

ORC Doctoral Students

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.

Bio: Miles Lubin is a fifth-year Ph.D. candidate in Operations Research at MIT advised by Juan Pablo Vielma. He received his B.S. in Applied Mathematics and M.S. in Statistics from the University of Chicago in 2011. After graduating, he spent a year as a researcher at Argonne National Laboratory before starting at MIT. His research interests span diverse areas of mathematical optimization, with a unifying theme of developing new methodologies for large-scale optimization drawing from motivating applications in renewable energy. He has published work in chance constrained optimization, mixed-integer conic optimization, robust optimization, stochastic programming, algebraic modeling, automatic differentiation, numerical linear algebra, and parallel computing techniques for large-scale problems. He is a co-founder of the JuliaOpt organization which has brought together early adopters in academia and industry with the goal of developing high quality open-source software for optimization in Julia.

Joey Huchette is a PhD student in the Operations Research Center at MIT, advised by Juan Pablo Vielma. He is supported by the NSF Graduate Fellowship. He received his B.A. in Applied Mathematics from Rice University, where he worked with Beatrice Riviere and Hadley Wickham. He studies operations research, specifically the theory and application of optimization. Much of his current work is concerned with mathematical formulations: that is, how to translate a high-level optimization problem to a mathematical description we can solve efficiently. He is also interested in all aspects of computational optimization, especially user-facing tools for modeling and for developing advanced algorithms.

In 2012, Miles Lubin, together with Iain Dunning and later joined by Joey Huchette, started developing JuMP, an open-source algebraic modeling language for optimization. Since then, JuMP has been used for teaching in at least 10 universities and by numerous researchers and companies worldwide. They were recently awarded the INFORMS Computing Society prize for this work.

Event Time: 

2017 - 16:15