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A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA

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A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA

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Pajares-Ferrando, A.; Blasco, X.; Herrero Durá, JM.; Reynoso-Meza, G. (2018). A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA. Complexity. 2018:1-22. https://doi.org/10.1155/2018/1792420

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/133380

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Title: A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Issued date:
Abstract:
[EN] Traditionally, in a multiobjective optimization problem, the aim is to find the set of optimal solutions, the Pareto front, which provides the decision-maker with a better understanding of the problem. This results ...[+]
Copyrigths: Reconocimiento (by)
Source:
Complexity. (issn: 1076-2787 )
DOI: 10.1155/2018/1792420
Publisher:
John Wiley & Sons
Publisher version: https://doi.org/10.1155/2018/1792420
Thanks:
This work was partially supported by the Ministerio de Economia y Competitividad (Spain) Grant numbers DPI2015-71443-R and FPU15/01652, by the local administration Generalitat Valenciana through the project GV/2017/029, ...[+]
Type: Artículo

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