Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization

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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization

Solving complex optimization problems can be painstakingly difficult endeavor considering multiple and conflicting design goals. A growing trend in utilizing meta-heuristic algorithms to solve these problems has been observed as they have shown considerable success in dealing with tradeoffs between...

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Bibliographic Details
Main Author:	Kamal Z., Zamli
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2018
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/23080/ http://umpir.ump.edu.my/id/eprint/23080/1/Enhancing%20generality%20of%20meta-heuristic%20algorithms%20through%20adaptive%20selection%20and%20hybridization.pdf

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