MultiJuMP.jl
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anriseth
MultiJuMP enables the user to easily run multiobjective optimisation problems and generate Pareto fronts.
Hi, I would like to run an ILP model with three objectives. the problem in the types.jl, the Phi is fixed at two dimensions, as using WeightedSum method, i can...
I'm using the Weighted Sum method of the the package MultiJuMP. Normally I generate a set on non-dominated solutions. However, in running the my ILP model with the weighted sum...
Hello, I have Integer Linea rmode with two variables and three objective. I'm using Weighted-Sum method to generate the pareto front points. So, I would like to show the value...
Hello, I executed an ILP model with three-objectives using the weighted sum method and i got a paretofront. The problem that i would like to show the used weights for...
Moved from README.md: - For 3 objectives or more: Make it possible to have different spacing in the components of $\beta$
Do you think it would be possible to support Benson's algorithm (in a similar way to [bensolve](http://bensolve.org/)) in `MultiJuMP` when the model is detected to be linear ? It could...
Moved from README.md. References: - http://epubs.siam.org/doi/abs/10.1137/060672029 - https://books.google.co.uk/books?id=IXsvG2DcbsAC
Moved from README.md: - Add objective `t` before the individual optimisations? * Then we can warm-start the NBI subproblems after the individual runs? * It seemed to cause an issue...
Moved from README.md: - Add bounds on the MultiObjective type (So we can ask to only search over subset of pareto front ) * __This seems to be causing problems...
Add the possibility to add penalty terms. Useful if the user wants to control constraint-violation themselves.