<div class="csl-bib-body">
<div class="csl-entry">Kühn, E., & Šešum-Čavić, V. (2022). A Framework-Based Approach for Flexible Evaluation of Swarm-Intelligent Algorithms. In A. E. Smith (Ed.), <i>Women in Computational Intelligence</i> (pp. 393–412). Springer. https://doi.org/10.1007/978-3-030-79092-9_18</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/148189
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dc.description.abstract
Many important Information Technology (IT) problems comprise some kind of optimization task that is challenging from the computation point of view and therefore needs to be addressed by an appropriate metaheuristic algorithm. Recently, a diversity of promising swarm-inspired metaheuristics appeared. However, the decision about what algorithm fits best for which class of problems and the fair comparison of a variety of algorithms are not clearly articulated from the methodological point of view. The usual approach taken is to integrate a certain algorithm into the solution for a concrete problem and to evaluate its usefulness. The deficiency of this approach is that such specialized solutions hardly allow the comparison of different algorithms under changing environmental conditions. In this chapter, we propose a new methodology for the evaluation of algorithms that are suited for highly dynamic scenarios requiring self-organization. The solution is based on a coordination middleware architecture that is used for the implementation of flexible and pattern-based frameworks and test beds. The evaluation is carried out by means of several use cases.
en
dc.language.iso
en
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dc.subject
swarm-inspired algorithms
en
dc.subject
methodology for evaluation of algorithms
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dc.subject
recommendation of algorithm for given use case
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dc.subject
coordination middleware
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dc.subject
Self-organization
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dc.subject
Distributed middleware architectures
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dc.subject
Coordination Patterns
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dc.title
A Framework-Based Approach for Flexible Evaluation of Swarm-Intelligent Algorithms
en
dc.type
Book Contribution
en
dc.type
Buchbeitrag
de
dc.relation.publication
Women in Computational Intelligence
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dc.contributor.editoraffiliation
Auburn University, United States of America (the)
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dc.relation.isbn
978-3-030-79092-9
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dc.relation.issn
2509-6427
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dc.description.startpage
393
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dc.description.endpage
412
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dcterms.dateSubmitted
2021-01-01
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dc.type.category
Edited Volume Contribution
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dc.relation.eissn
2509-6435
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tuw.booktitle
Women in Computational Intelligence
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tuw.book.ispartofseries
Women in Engineering and Science
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tuw.relation.publisher
Springer
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tuw.relation.publisherplace
Cham
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tuw.book.chapter
18
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tuw.researchTopic.id
C4
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-05 - Forschungsbereich Compilers and Languages
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tuw.publisher.doi
10.1007/978-3-030-79092-9_18
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dc.description.numberOfPages
20
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
50
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wb.sciencebranch.value
50
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item.openairecristype
http://purl.org/coar/resource_type/c_3248
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item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.grantfulltext
none
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item.openairetype
book part
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item.languageiso639-1
en
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crisitem.author.dept
E194-05 - Forschungsbereich Compilers and Languages
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crisitem.author.dept
E194 - Institut für Information Systems Engineering
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering