VOptSpecific.jl

Solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO): specific part
Author vOptSolver
Popularity
4 Stars
Updated Last
2 Years Ago
Started In
June 2017

vOptSpecific: part of vOptSolver for structured problems

Build Status codecov.io

vOptSolver is a solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO). This repository concerns vOptSpecific, the part of vOptSolver devoted to multiobjective structured problems (currently available: 2LAP, 2OSP, 2UKP, 2UMFLP). With vOptSpecific, the problem is expressed using an Application Programming Interface. vOptSpecific runs on macOS, and linux-ubuntu.

We suppose you are familiar with vOptSolver; if not, read first this presentation.

Instructions

For an use, a working version of:

  • Julia must be ready; instructions for the installation are available here
  • your favorite C/C++ compiler must be ready (GCC is suggested)

Run Julia

On linux:

  • 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

Installation Instructions

Before your first use,

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

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

Usage Instructions

When vOptSpecific is properly installed,

  1. run Julia and when the terminal is ready with the prompt julia on screen,
  2. invoke vOptSpecific in typing in the console:
julia> using vOptSpecific

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

Problems available:

Problem Description API src Reference
LAP Linear Assignment Problem 2LAP2008 C Przybylski2008
OSP One machine Scheduling Problem 2OSP1980 Julia Wassenhove1980
UKP 01 Unidimensional knapsack problem 2UKP2010 Julia Jorge2010
UMFLP Uncapacitated Mixed variables Facility Location Problem 2UMFLP2016 C++ Delmee2017

Examples

The folder examples provides (1) source code of problems ready to be solved and (2) selected datafiles into different formats.

Limitations

  • The problem size for 2LAP is limited to 100x100.