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dc.contributor.authorDel Ser, J. 
dc.contributor.authorBenítez-Hidalgo, A.
dc.contributor.authorJ. Nebro, A.
dc.contributor.authorGarcía-Nieto, J.
dc.contributor.authorOregi, I.
dc.date.accessioned2020-10-14T11:16:15Z
dc.date.available2020-10-14T11:16:15Z
dc.date.issued2019-10-31
dc.identifier.issn2210-6502
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1162
dc.description.abstractThis paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques. Building upon our experiences with the well-known jMetal framework, we have developed a new multi-objective optimization software platform aiming not only at replicating the former one in a different programming language, but also at taking advantage of the full feature set of Python, including its facilities for fast prototyping and the large amount of available libraries for data processing, data analysis, data visualization, and high-performance computing. As a result, jMetalPy provides an environment for solving multi-objective optimization problems focused not only on traditional metaheuristics, but also on techniques supporting preference articulation and dynamic problems, along with a rich set of features related to the automatic generation of statistical data from the results generated, as well as the real-time and interactive visualization of the Pareto front approximations produced by the algorithms. jMetalPy offers additionally support for parallel computing in multicore and cluster systems. We include some use cases to explore the main features of jMetalPy and to illustrate how to work with it.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectMulti-ObjectiveOptimizationen_US
dc.subjectMetaheuristicsen_US
dc.subjectSoftwareFrameworken_US
dc.subjectPythonen_US
dc.subjectStatisticalAnalysisen_US
dc.subjectVisualizationen_US
dc.titlejMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristicsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doihttps://doi.org/10.1016/j.swevo.2019.100598
dc.relation.publisherversionhttps://jmetal.github.io/jMetalPy/index.htmlen_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen_US
dc.journal.titleSwarm and Evolutionary Computationen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España