vOptSolver is a solver of multiobjective linear optimization problems (MOCO, MOIP, MOMILP, MOLP). This repository concerns vOptGeneric, the part of vOptSolver devoted to multiobjective non-structured problems (currently available: 2IP). With vOptGeneric, the problem is expressed using JuMP algebraic language extended to multiple objectives.
We suppose you are familiar with vOptSolver; if not, read first this presentation.
For a local use, a working version of:
- Julia must be ready; instructions for the installation are available here
- your favorite MILP solver must be ready (GLPK is suggested); instructions for the installation are available here
On linux or in the cloud (juliaBox):
- open a console on your computer or in the cloud
- when the prompt is ready, type in the console
julia
On macOS:
- locate the application
julia
and - click on the icon, the julia console comes to the screen
Before your first local or distant use,
- run Julia and when the terminal is ready with the prompt
julia
on screen, - add as follow the two mandatory packages to your Julia distribution:
julia> Pkg.clone("http://github.com/vOptSolver/vOptGeneric.jl")
julia> Pkg.add("GLPK") ; Pkg.add("GLPKMathProgInterface")
That's all folk; at this point, vOptGeneric is properly installed.
When vOptGeneric is properly installed,
- run Julia and when the terminal is ready with the prompt
julia
on screen, - invoke vOptGeneric and the MILP solver to activate in typing in the console:
julia> using vOptGeneric
julia> using GLPK ; using GLPKMathProgInterface
vOptGeneric is ready. See examples for further informations and have fun with the solver!
The folder examples
provides (1) source code of problems ready to be solved and (2) selected datafiles into different formats.
No special limitation; the solving strength of vOptGeneric is currently provided by the MILP solver (GLPK, CPLEX, etc.) invoked.