Real-world problems require sophisticated methodologies providing feasible and efficient solutions. Metaheuristics are algorithms proposed to approximate those optimal solutions in a short time, making them suitable for applications where saving time is important. Metaheuristics.jl package implements relevant state-of-the-art algorithms for constrained, multi-, many-objective and bilevel optimization. Moreover, performance indicators are implemented in this package.
This talk presents the main features of Metaheuristics.jl, which is a package for global optimization to approximate solutions for single-, multi-, and many-objective optimization. Several examples are given to illustrate the implementation and the resolution of the different optimization problems.