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The information in our interactive Radar is currently only available in English. To get information in your native language, please download the PDF here.

NOT ON THE CURRENT EDITION
This blip is not on the current edition of the radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the radarUnderstand more
Mar 2017
assess?

JuMP is a domain-specific language for mathematical optimizations in Julia. JuMP defines a common API called MathProgBase and enables users to write solver-agnostic code in Julia. Currently supported solvers include Artelys Knitro, Bonmin, Cbc, Clp, Couenne, CPLEX, ECOS, FICO Xpress, GLPK, Gurobi, Ipopt, MOSEK, NLopt and SCS. One other benefit is the implementation of automatic differentiation technique in reverse mode to compute derivatives so users are not limited to the standard operators like sin, cos, log and sqrt but can also implement their own custom objective functions in Julia.

Nov 2016
assess?

JuMP is a domain-specific language for mathematical optimizations in Julia. JuMP defines a common API called MathProgBase and enables users to write solver-agnostic code in Julia. Currently supported solvers include Artelys Knitro, Bonmin, Cbc, Clp, Couenne, CPLEX, ECOS, FICO Xpress, GLPK, Gurobi, Ipopt, MOSEK, NLopt and SCS. One other benefit is the implementation of automatic differentiation technique in reverse mode to compute derivatives so users are not limited to the standard operators like sin, cos, log and sqrt but can also implement their own custom objective functions in Julia.