Skip to content

Solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO): generic part

License

Notifications You must be signed in to change notification settings

vOptSolver/vOptGeneric.jl

Repository files navigation

vOptGeneric: part of vOptSolver for non-structured problems

Build Status codecov.io Coverage Status

vOptSolver is a solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO). This repository concerns vOptGeneric, the part of vOptSolver devoted to multiobjective non-structured problems. With vOptGeneric, the problem is expressed using JuMP algebraic language extended to multiple objectives. vOptGeneric runs on macOS, linux-ubuntu, and windows. We suppose you are familiar with vOptSolver; if not, read first this presentation.

IMPORTANT (Feb-2023):

vOptGeneric.jl has been fully redesigned, and reimplemented. It becomes MultiObjectiveAlgorithms.jl (MOA), a collection of algorithms for multi-objective optimization integrated to JuMP and MathOptInterface. MOA comes with an enriched list of multi-objective algorithms, especially for solving problems with 3 objectives. Examples are available here:

Consequently vOptGeneric.jl is no longer under active development. It will remain available on Github at this URL. From February 2023, the JuMP-dev organization will continue to maintain the MOA package and transition development over the long term.

Instructions

For a local use, a working version of:

  • Julia must be ready; instructions for the installation are available here
  • your favorite MIP solver must be ready (GLPK is suggested); instructions for the installation are available here

Run Julia

On linux:

  • open a console on your computer
  • 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

Installation Instructions

Before your first use,

  1. run Julia and when the terminal is ready with the prompt julia on screen,
  2. add as follow the mandatory packages to your Julia distribution:
julia> using Pkg
julia> Pkg.add("vOptGeneric")
julia> Pkg.add("JuMP")
julia> Pkg.add("GLPK")

That's all folk; at this point, vOptGeneric is properly installed.

Usage Instructions

When vOptGeneric is properly installed,

  1. run Julia and when the terminal is ready with the prompt julia on screen,
  2. invoke vOptGeneric, JuMP and the MILP solver to activate in typing in the console:
julia> using vOptGeneric
julia> using JuMP
julia> using GLPK

vOptGeneric is ready. See examples for further informations and have fun with the solver!

Problems available

Problem Description Output Method Parameter (if required) Name
2-IP bi-objective Integer Linear Program Y_N :epsilon step = realValue ϵ-constraint
2-IP bi-objective Integer Linear Program Y_N :chalmet or :Chalmet step = realValue Chalmet
2-IP bi-objective Integer Linear Program Y_{SN} :dicho or :dichotomy (none) Aneja & Nair
p-MIP multi-objective Mixed Integer Linear Program Y_{lex} :lex or :lexico (none) Lexicographic

Examples

The folder examples provides source code of problems ready to be solved.

Validation

Tested the

  • 22-Jul-2021

with

  • Julia 1.6.2
  • JuMP 0.21.8
  • GLPK 4.65
  • Gurobi 9.1.2

on

  • Linux ubuntu 18.04.5 LTS
  • macOS 11.4 (Big Sur)
  • Windows 10

About

Solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO): generic part

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •  

Languages