EmiR: Evolutionary minimization 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 nature-inspired...

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Bibliographic Details
Published inSoftwareX Vol. 18; p. 101083
Main Authors Pagano, Davide, Sostero, Lorenzo
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.06.2022
Elsevier
Subjects
Evolutionary algorithms
Optimization
R
Optimization
Evolutionary algorithms
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Summary: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 nature-inspired 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. [Display omitted]
ISSN:2352-7110
2352-7110
DOI:10.1016/j.softx.2022.101083