EmiR: Evolutionaryminimization for R

Classical minimization methods, like the steepest descent or quasi-Newton techniques, have been proved to struggle in dealing with optimization problems with a high-dimensional search space or subject to complex nonlinear constraints. In the last decade, the interest on metaheuristic natureinspired algorithms has been growing steadily, due to their flexibility and effectiveness. In this paper we present EmiR, a package for R which implements several metaheuristic algorithms for optimization problems. Unlike other available tools, EmiR can be used not only for unconstrained problems, but also for problems subjected to inequality constraints and for integer or mixed-integer problems. Main features of EmiR, its usage and the comparison with other available tools are presented. © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Code metadata Current code version v1.0.3 Permanent link to code/repository used for this code version https://github.com/ElsevierSoftwareX/SOFTX-D-22-00026 Legal Code License GNU General Public License (GPL) Code versioning system used git Software code languages, tools, and services used C++, R Support email for questions davide.pagano@unibs.it