<div class="csl-bib-body">
<div class="csl-entry">Raidl, G., Puchinger, J., & Blum, C. (2019). Metaheuristic Hybrids. In M. Gendreau & J.-Y. Potvin (Eds.), <i>Handbook of Metaheuristics</i> (Vol. 272, pp. 385–417). Springer. https://doi.org/10.1007/978-3-319-91086-4_12</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/30453
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dc.description.abstract
Over the last decades, so-called hybrid optimization approaches have become
increasingly popular for addressing hard optimization problems. In fact, when
looking at leading applications of metaheuristics for complex real-world scenarios,
many if not most of them do not purely adhere to one specific classical metaheuristic
model but rather combine different algorithmic techniques. Concepts from different
metaheuristics are often hybridized with each other, but they are also often combined
with other optimization techniques such as tree-search, dynamic programming and
methods from the mathematical programming, constraint programming, and SATsolving
fields. Such combinations aim at exploiting the particular advantages of the
individual components, and in fact well-designed hybrids often perform substantially
better than their "pure" counterparts. Many very different ways of hybridizing
metaheuristics are described in the literature, and unfortunately it is usually difficult
to decide which approach(es) are most appropriate in a particular situation. This
chapter gives an overview on this topic by starting with a classification of metaheuristic
hybrids and then discussing several prominent design templates which are
illustrated by concrete examples.
G
en
dc.publisher
Springer
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dc.title
Metaheuristic Hybrids
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dc.type
Buchbeitrag
de
dc.type
Book Contribution
en
dc.relation.publication
Handbook of Metaheuristics
-
dc.contributor.editoraffiliation
Ecole Polytechnique de Montréal
-
dc.contributor.editoraffiliation
Département d’informatique et de recherche opérationnelle, Université de Montréal, Montreal, Canada
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dc.relation.isbn
978-3-319-91086-4
-
dc.relation.doi
10.1007/978-3-319-91086-4
-
dc.relation.issn
0884-8289
-
dc.description.startpage
385
-
dc.description.endpage
417
-
dc.type.category
Edited Volume Contribution
-
dc.relation.eissn
2214-7934
-
tuw.booktitle
Handbook of Metaheuristics
-
tuw.container.volume
272
-
tuw.peerreviewed
true
-
tuw.book.ispartofseries
International Series in Operations Research & Management Science
-
tuw.relation.publisher
Springer
-
tuw.relation.publisherplace
Cham
-
tuw.book.chapter
12
-
tuw.researchTopic.id
I1
-
tuw.researchTopic.name
Logic and Computation
-
tuw.researchTopic.value
100
-
tuw.publication.orgunit
E192-01 - Forschungsbereich Algorithms and Complexity
-
tuw.publisher.doi
10.1007/978-3-319-91086-4_12
-
dc.description.numberOfPages
33
-
tuw.editor.orcid
0000-0002-9262-3648
-
wb.sciencebranch
Informatik
-
wb.sciencebranch.oefos
1020
-
wb.facultyfocus
Logic and Computation (LC)
de
wb.facultyfocus
Logic and Computation (LC)
en
wb.facultyfocus.faculty
E180
-
item.openairecristype
http://purl.org/coar/resource_type/c_3248
-
item.grantfulltext
none
-
item.openairetype
book part
-
item.fulltext
no Fulltext
-
item.cerifentitytype
Publications
-
crisitem.author.dept
E192-01 - Forschungsbereich Algorithms and Complexity