Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00198965" target="_blank" >RIV/68407700:21230/12:00198965 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-642-29124-1_13?LI=true" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-642-29124-1_13?LI=true</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-29124-1_13" target="_blank" >10.1007/978-3-642-29124-1_13</a>

Result language
angličtina
Original language name
Hyper-Heuristic Based on Iterated Local Search Driven by Evolutionary Algorithm
Original language description
This paper proposes an evolutionary-based iterative local search hyper-heuristic approach called Iterated Search Driven by Evolutionary Algorithm Hyper-Heuristic (ISEA). Two versions of this algorithm, ISEA-chesc and ISEA-adaptive that differ in the re-initialization scheme are presented. The performance of the two algorithms was experimentally evaluated on six hard optimization problems using the HyFlex experimental framework and the algorithms were compared with algorithms that took part in the CHeSC2011 challenge. Achieved results are very promising; the ISEA-adaptive would take the second place in the competition. It shows how important for good performance of this iterated local search hyper-heuristic is the re-initialization strategy.
Czech name
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Czech description
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Evolutionary Computation in Combinatorial Optimization
ISBN
978-3-642-29123-4
ISSN
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e-ISSN
—
Number of pages
12
Pages from-to
148-159
Publisher name
Springer
Place of publication
Heidelberg
Event location
Málaga
Event date
Apr 11, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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