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Last updated : Mar 29, 2017
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 Radar. Understand more
Mar 2017
Assess ? Worth exploring with the goal of understanding how it will affect your enterprise.

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 ? Worth exploring with the goal of understanding how it will affect your enterprise.

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.

Published : Nov 07, 2016

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