Inferring Parameters of a Relational System of Preferences from Assignment Examples using an Evolutionary Algorithm

Inferring Parameters of a Relational System of Preferences from Assignment Examples using an Evolutionary Algorithm

Most evolutionary multi-objective algorithms perform poorly in many-objective problems. They normally do not make selective pressure towards the Region of Interest (RoI), the privileged zone in the Pareto frontier that contains solutions important to a DM. Several works have proved that a priori inc...

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書誌詳細
第一著者:	Fernández, Eduardo
その他の著者:	Sanchez Solis, Julia Patricia, Rivera Zarate, Gilberto
フォーマット:	Artículo
言語:	en_US
出版事項:	2019
主題:	decision making multi-objective optimization evolutionary algorithms parameter elicitation fuzzy preferences outranking methods info:eu-repo/classification/cti/1
オンライン･アクセス:	https://doi.org/10.3846/tede.2019.9475 https://journals.vgtu.lt/index.php/TEDE/article/view/9475
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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