Solver of multiobjective linear optimization problems: description and documents

View the Project on GitHub vOptSolver/vOptSolver

Solver of multiobjective linear optimization problems

vOptSolver is an ecosystem for modeling and solving multiobjective linear optimization problems (MOCO, MOIP, MOMIP, MOLP). It has been supported by the ANR/DFG-14-CE35-0034-01 research project (link). It integrates several exact algorithms for computing a complete set of non-dominated points for structured and non-structured optimization problems with at least two objectives.

This repository (1) gives a description of the solver and (2) hosts documents covering all parts of the solver.



22-Apr-2019: Preparing an update of the documentation 
31-Oct-2018: vOptSpecific and vOptGeneric are compliant with Julia v1.x 
01-Jul-2018: Preparing the switch to Julia 0.7 and to the new version of JuMP 
01-Sep-2017: Algorithms added to vOptGeneric and vOptSpecific, documentation and examples are coming.
20-Jul-2017: Examples presented in conferences (MCDM'2017; IFORS'2017) are online (folder examples)
26-Jun-2017: Source codes of vOptGeneric and vOptSpecific for v0.0.2 are online
17-Jun-2017: Moved from GitLab to GitHub
03-Jun-2017: The next release (v0.0.2) is scheduled for June 2017


All bugs, feature requests, pull requests, feedback, etc., are welcome.


Prof. Dr. Xavier Gandibleux, University of Nantes - France (contact)


By chronological order:

How To Contribute

  1. in adding your examples (code JuMP + data) solved with vOptGeneric to the collection;
  2. in plugging your own C/C++/Julia algorithms into vOptSpecific or vOptGeneric;
  3. in adapting vOptSpecific for windows;
  4. in sending us your suggestions to improve/extend vOptSolver;
  5. in telling us when you have completed a work (exercices for students; research; paper; etc.) using vOptSolver;
  6. in joining the adventure with us as maintainer of the solver, repositories, documents, etc.

In brief, every contributions aiming to share our efforts, our algorithms, our productions around this open source software are welcome.


vOptSolver is distributed under the MIT License.

How To Cite

Xavier Gandibleux, Gauthier Soleilhac, Anthony Przybylski, Flavien Lucas, Stefan Ruzika, Pascal Halffmann. vOptSolver, a “get and run” solver of multiobjective linear optimization problems built on Julia and JuMP. MCDM2017: 24th International Conference on Multiple Criteria Decision Making. July 10-14, 2017. Ottawa (Canada).

Xavier Gandibleux, Gauthier Soleilhac, Anthony Przybylski, Stefan Ruzika. vOptSolver: an open source software environment for multiobjective mathematical optimization. IFORS2017: 21st Conference of the International Federation of Operational Research Societies. July 17-21, 2017. Quebec City (Canada).


The development of vOptSolver started in the ANR/DFG-14-CE35-0034-01 research project vOpt (link) involving Université de Nantes (France) and University of Koblenz-Landau/University of Kaiserslautern (Germany).







Problems managed

Algorithms integrated

The solving algorithms included compute exact solution(s) corresponding to Y_{lex}, Y_{SN}, or Y_{N}.





Installation and usage Instructions

Refer to the instructions provided for

Documentation (working on it)

The documentation has been written for Julia v0.6.4. New versions compliant with v1.x are for soon. We apologize if some examples raise an error.


Terms and acronyms used