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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| Published in | SoftwareX Vol. 18; p. 101083 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
01.06.2022
Elsevier |
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| Online Access | Get full text |
| ISSN | 2352-7110 2352-7110 |
| DOI | 10.1016/j.softx.2022.101083 |
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| Abstract | 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.
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| AbstractList | 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] 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. |
| ArticleNumber | 101083 |
| Author | Pagano, Davide Sostero, Lorenzo |
| Author_xml | – sequence: 1 givenname: Davide orcidid: 0000-0003-0333-448X surname: Pagano fullname: Pagano, Davide email: davide.pagano@unibs.it – sequence: 2 givenname: Lorenzo surname: Sostero fullname: Sostero, Lorenzo email: l.sostero@studenti.unibs.it |
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| Cites_doi | 10.1007/s10898-007-9149-x 10.1016/j.compstruc.2004.01.002 10.1016/j.advengsoft.2016.01.008 10.1137/S1052623496303470 10.1007/BF00930579 10.1016/0305-0548(86)90048-1 10.6028/jres.049.044 10.1016/j.beproc.2011.09.006 10.1007/s10462-017-9605-z 10.1126/science.220.4598.671 10.1007/s10589-005-0985-7 10.1016/j.knosys.2015.07.006 10.1016/0895-7177(96)00014-3 10.1177/003754970107600201 10.1145/29380.29864 10.1016/j.ins.2009.03.004 10.4249/scholarpedia.6532 10.1016/j.advengsoft.2013.12.007 |
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