vOptSolver is an open source ecosystem written in the Julia language, for modeling and solving multi-objective linear optimization problems (mixed integer problems, continuous problems, integer problems, and combinatorial problems). Currently vOptSolver is composed of two independant packages named vOptGeneric.jl and vOptSpecific.jl integrated and registered as Julia packages since 2017. The source codes, examples, documentation and tutorial are available at https://github.com/vOptSolver.
vOptSolver is aimed to be a software for scientifics and practionners. It has been conceived to be intuitive for various profile of users (mathematicians, informaticians, and engineers), corresponding to needs encountered in research and development (open-source codes available for the design of new algorithms), decision-making (ready-to-use methods and algorithms for solving optimization problems), and education (environment for teachning and practicing the theories and algorithms).
The optimization problem to solve is built in formulating a model with the algebraic modeling language JuMP, extended to support multi-objective models, for non-structured optimization problems, or in calling the corresponding API for structured optimization problems. The problem data and the optimization results are set on and handled by the datastructures and functionalities of Julia.
vOptSolver integrates several generic and specific algorithms of the literature for computing the set of exact non-dominated points. It returns also the efficient solutions corresponding to this set. The generic algorithms make use of a MIP solver, while specific algorithms call problem-dedicated algorithms.
I. Dunning, J. Huchette, M. Lubin, JuMP: A Modeling Language for Mathematical Optimization, SIAM Review 59 (2) (2017) 295–320.
B. Legat, O. Dowson, J. D. Garcia, M. Lubin, MathOptInterface: a data structure for mathematical optimization problems (2020). arXiv:2002.03447
X. Gandibleux, G. Soleilhac, A. Przybylski, S. 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). (2017).