I find JuMP.set_objective_coefficient somewhat favorable, because it is a functional API, and is flexible. e.g., I can use it to write a (pseudo-) Benders’ decomposition algorithm import JuMP, Gurobi; GRB_ENV = Gurobi.Env(); function Model(name) # e.g. "st2_lms" or "st1_bMD" or "supp_lMs" m = J…

For 1, do: f = objective_function(model) coefficient(f, x) I don’t want to add objective_function_coefficient(model, x) because this implies that we can efficiently query an objective coefficient, which we cannot do. We have added normalized_coefficient for constraints, but I tend to think this wa…

Can we improve JuMP.set_objective_coefficient?

Specific Domains Optimization (Mathematical)

odow April 3, 2025, 1:52am 6

I’m going to link you to PSA: Julia is not at that stage of development anymore. It’s written for Julia, but the same logic applies to JuMP.

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Can we improve JuMP.set_objective_coefficient?

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